Functional properties of enzymatically modified protein from fish waste

Fish flour from dried waste consisting of head, tail, fins and entrails was enzimatically hydrolysed using various proteases and the hydrolysate was spray dried. The functional properties such as water-fat absorption ratio, foaming and solubility index of the hydrolysates and fish flour revealed that some of the products might find significant uses in the food and/or cosmetics industry. Electrophoretic separation of the proteins from the fish flour and of the hydrolysates indicated that almost all the flour proteins are susceptible to proteolytic cleavage with the exception of one or two. The extent of degree of hydrolysis from 43-70.3% with a simultaneous decrease in unpleasant smell suggest an economical tool for minimizing odour pollution due to fish industry waste deterioration.

Modified Kanerva model. Results for real time word recognition

This paper describes results obtained using the modified Kanerva model to perform word recognition in continuous speech after being trained on the multi-speaker Alvey 'Hotel' speech corpus. Theoretical discoveries have recently enabled us to increase the speed of execution of part of the model by two orders of magnitude over that previously reported by Prager & Fallside. The memory required for the operation of the model has been similarly reduced. The recognition accuracy reaches 95% without syntactic constraints when tested on different data from seven trained speakers. Real time simulation of a model with 9,734 active units is now possible in both training and recognition modes using the Alvey PARSIFAL transputer array. The modified Kanerva model is a static network consisting of a fixed nonlinear mapping (location matching) followed by a single layer of conventional adaptive links. A section of preprocessed speech is transformed by the non-linear mapping to a high dimensional representation. From this intermediate representation a simple linear mapping is able to perform complex pattern discrimination to form the output, indicating the nature of the speech features present in the input window.

The modified Kanerva model for automatic speech recognition

A parallel processing network derived from Kanerva's associative memory theory Kanerva 1984 is shown to be able to train rapidly on connected speech data and recognize further speech data with a label error rate of 0·68%. This modified Kanerva model can be trained substantially faster than other networks with comparable pattern discrimination properties. Kanerva presented his theory of a self-propagating search in 1984, and showed theoretically that large-scale versions of his model would have powerful pattern matching properties. This paper describes how the design for the modified Kanerva model is derived from Kanerva's original theory. Several designs are tested to discover which form may be implemented fastest while still maintaining versatile recognition performance. A method is developed to deal with the time varying nature of the speech signal by recognizing static patterns together with a fixed quantity of contextual information. In order to recognize speech features in different contexts it is necessary for a network to be able to model disjoint pattern classes. This type of modelling cannot be performed by a single layer of links. Network research was once held back by the inability of single-layer networks to solve this sort of problem, and the lack of a training algorithm for multi-layer networks. Rumelhart, Hinton & Williams 1985 provided one solution by demonstrating the "back propagation" training algorithm for multi-layer networks. A second alternative is used in the modified Kanerva model. A non-linear fixed transformation maps the pattern space into a space of higher dimensionality in which the speech features are linearly separable. A single-layer network may then be used to perform the recognition. The advantage of this solution over the other using multi-layer networks lies in the greater power and speed of the single-layer network training algorithm. © 1989.

Effect of modified starch on the shelf life of frozen fish Kamaboko with prepared spinach

Fish kamaboko with spinach was prepared by mixing fish kamaboko with spinach prepared with different combinations of ordinary starch (OS) and modified starch (MS), viz., 40:60, 50:50, 60:40, 100%) MS and 100% OS. The products were frozen at -40°C and stored at -20°C, and subjected to biochemical (peroxide value, total titratable acidity, pH and moisture) organoleptic (appearance, taste and colour), microbiological (total plate count) and physical (folding and expressible water) tests at monthly intervals. Among the different combinations tried, it was observed that fish kamaboko with spinach prepared with 50:50 and 60:40 combinations of OS and MS could be stored for six months at-20°C.

Modified water spray chumming system for pole and line fishing of tuna

A water spray chumming system consisting of a 65 x 50 mm centrifugal pump driven by the propulsion engine through a PTO clutch and 'V' pulley power transmission system has been developed for the pole and line fishing of tuna. Water is sprayed through pipe loop system fitted on the edge of the fishing platform of the boat through small holes. The distance of the spray length can be adjusted by controlling the flow of the pump discharge water through a wheel valve.

Study on the sustainability of FPC produced from Kilka (Clupeonella engrauliformis, C. grimmi and C. cultriventris) in two vacuum packaging and modified atmosphere packaging at different environmental factors

Fish protein concentrate (FPC) is a healthy, sustainable and high nutritive product which sanitized produced from fishes in which, protein and other nutrients are more concentrated than in fresh fishes. The aim of this research is to study on the sustainability of FPC produced from Kilka (Clupeonella engrauliformis , C. grimmi and C. cultriventris) in two Vaccum Packaging and Modified Atmosphere Packaging at different environmental factors during six months. In our study the analysis of FPC protein showed 91.2%, lipid: 0.5%, ash: 3.6%, moisture: 2.3%, Total Volatile Nitrogen: 10 ml/100gr and peroxide: 5meq/kg. Amino acids and fatty acids were also determined. Bacteria and Fungi were lower than 1000 colony. Samples are kept in different condition of temperature (5, 20 and 35 degree centigrade), humidity (25, 40 and 90 percent) and light and dark environment in six month. Lipid rate in FPC after 6 months in VP and MAP (60% C02, 30 % N2 and 10% O2), packages was decreased but was not significant (P>0.05). It was also detected that increase temperature lead to more decrease in lipid content. Protein rate of FPC was decreased from 91.2% to 73.6% during six months at 35°C in VP Package and from 91.2% to 69.4% in MAP package. These changes were significant (P<0.05). TVN and PV rate in FPC after 6 months in VP and MAP packages was increased but was significant (P<0.05). Amino acids and fatty acids were also determined. But more changes in MAP packages was detected.

Analysis of CFRP strap-strengthened reinforced concrete beams using the modified compression field theory (MCFT)

External, prestressed carbon fiber reinforced polymer (CFRP) straps can be used to enhance the shear strength of existing reinforced concrete beams. In order to effectively design a strengthening system, a rational predictive theory is required. The current work investigates the ability of the modified compression field theory (MCFT) to predict the behavior of rectangular strap strengthened beams where the discrete CFRP strap forces are approximated as a uniform vertical stress. An unstrengthened control beam and two strengthened beams were tested to verify the predictions. The experimental results suggest that the MCFT could predict the general response of a strengthened beam with a uniform strap spacing < 0.9d. However, whereas the strengthened beams failed in shear, the MCFT predicted flexural failures. It is proposed that a different compression softening model or the inclusion of a crack width limit is required to reflect the onset of shear failures in the strengthened beams.

Development of accurate, robust liquid equations of state for multi-phase CFD simulations with a modified AUSM+-up scheme

Eight equations of state (EOS) have been evaluated for the simulation of compressible liquid water properties, based on empirical correlations, the principle of corresponding states and thermodynamic relations. The IAPWS-IF97 EOS for water was employed as the reference case. These EOSs were coupled to a modified AUSM+-up convective flux solver to determine flow profiles for three test cases of differing flow conditions. The impact of the non-viscous interaction term discretisation scheme, interfacial pressure method and selection of low-Mach number diffusion were also compared. It was shown that a consistent discretisation scheme using the AUSM+-up solver for both the convective flux and the non-viscous interfacial term demonstrated both robustness and accuracy whilst facilitating a computationally cheaper solution than discretisation of the interfacial term independently by a central scheme. The simple empirical correlations gave excellent results in comparison to the reference IAPWS-IF97 EOS and were recommended for developmental work involving water as a cheaper and more accurate EOS than the more commonly used stiffened-gas model. The correlations based on the principles of corresponding-states and the modified Peng-Robinson cubic EOS also demonstrated a high degree of accuracy, which is promising for future work with generic fluids. Further work will encompass extension of the solver to multiple dimensions and to account for other source terms such as surface tension, along with the incorporation of phase changes. © 2013.