Changes in Protein, Carbohydrate and lipid content of cashew kernels during storage under two humidity conditions

The changes occuring to cashew kernels during storage at two humidity levels - 80% to 20% with respect to organoleptic characteristics, protein content, carbohydrate content, oil content, iodine and peroxide values were studied. From the present study it is concluded that organoleptic characteristics of cashew kernels deteriorates with increase in humidity. Decrease in protein and carbohydrate content of stored cashew kernel is dependent on humidity. Humidity increased oxidative rancidification.

Effect of Antioxidants on the Shelf Life of Cashew Kernels

Cashew kernels have high nutritive value. Upon exposure to air kernels turn rancid and their nutritive value decreases. From this study it is concluded that chemical treatment using antioxidants reduced oxidative rancidity but failed to prevent deterioration in organoleptic characteristics and decrease in protein and carbohydrate content of stored kernels.

Prediction of Key Symptoms of Learning Disabilities in School-Age Children Using Rough Sets

This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

Theory of Breaking of a Potyrner Molecule under Tension

The thesis presents the dynamics of a polymer chain under tension. It includes existing theories of polymer fracture, important theories of reaction rates, the rate using multidimensional transition state theory and apply it to the case of polyethylene etc. The main findings of the study are; the life time of the bond is somewhat sensitive to the potential lead to rather different answers, for a given potential a rough estimate of the rate can be obtained by a simples approximation that considers the dynamics of only the bond that breaks and neglects the coupling to neighboring bonds. Dynamics of neighboring bonds would decrease the rate, but usually not more than by one order of magnitude, for the breaking of polyethylene, quantum effects are important only for temperatures below 150K, the lifetime strongly depends on the strain and as the strain varies over a narrow range, the life varies rapidly from 105 seconds to 10_5 seconds, if we change one unit of the polymer by a foreign atom, say by one sulphure atom, in the main chain itself, by a weaker bond, the rate is found to increase by orders of magnitude etc.

Statistical Machine Learning Techniques for the Prediction of Learning Disabilities in School-Age Children

Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

Packaging materials for shrimp, fish and fish products, their properties, selection and effect of different packaging materials on their shelf life

Packaging is important not only in extending the shellife of fish and fishery products but also improving their marketability. In the recent years, significant development have taken place in the packaging industry. During the past decade in India, there is almost a packaging revolution with the availability of variety packaging materials, thus generating better packaging consciousness in other producer/manufacturing industries. But unfortunately, such realisation is not forthcoming in the fisheries sector and packaging techniques for local and export trade continues to be on traditional lines with their inherent drawbacks and limitations. Better packaging ensures improved quality and presentation of the products and ensures higher returns to the producer. Among several packaging materials used in fishery industry, ISI specifications had been formulated only for corrugated fibre board boxes for export of seafoods and froglegs. This standard was formulated before containersiation came into existance in the export of marine products. Before containerisation, the standards were stringent in view of the rough handling, transportation and storage. Two of the common defects reported in the master cartons exported from India are low mechanical strength and tendency to get wet. They are weakened by the deposits of moisture caused by temperature fluctuations during loading, unloading and other handling stages. It is necessary to rectify the above defects in packaging aquatic products and hence in the present study extensive investigations are carried out to find out the reasons for the damage of master cartons, to evolve code of practice for the packaging oi frozen shrimp for exports, development of alternative style of packaging for the shipping container, development of suitable consumer packaging materials for fish soup powder, cured dried mackeral, fish pickles in oil and frozen shrimp. For the development of suitable packaging materials, it is absolutely essential to know the properties of packaging materials, effect of different packaging materials on theirshelf life and their suitability for food contact applications.

A study of the cost structure of the cashew industry in kerala, karnataka and tamilnadu

Since the world demand for cashew kernels has been rising steadily for several years in the past, conferring significant price increase the processing of cashew remains a highly profitable lndustry. India being the earliest and largest supplier of cashew kernels in the world market it is our prestigious obligations to reestablish her pristine monopoly. Further the added importance ot the indutry in the Socio economic context of the State of Kerala makes various measures impervative in order to bring back to the industry its pristine glory at the late sixties to give a face lift and to stabilize the industry. This present study adopts a comprehensive frame work of analysis compassing the major issues involved in the cultivation, distribution, import, processing and marketing of cashew undcr the private and public sector, migration of the industry and the financial requirements of the industry.

Studies On Sediment Transport In The Surf Zone Along Certain Beaches Of Kerala

Sediment transport in the nearshore areas is an important process in deciding the coastline stability. The design and effective maintenance of navigable waterways, harbours and marine structures depend on the stability of the sediment substrate and the nature of sedimentation in the nearshore zone. The nearshore zone is a complex environment and the exact relationships existing between water motions and the resulting sediment transports are not well understood. During the rough weather season, when the sediment movement is considerable, processes occurring in the nearshore area are much less understood. Moreover, there is a general lack of field measurements, especially during the time of severe storm conditions. The increasing pressures and the concern on the preservation of the valuable coastal environment have led to the development of shore protection programmes. Conservation not only demands knowledge of what needs to be done, but also requires the basic processes to be fully understood. Considering the fragile nature of barrier beaches and intense occupancy of these areas by man, these coastal features have long been a subject of study by coastal oceanographers, geomorphologists and engineers. The present study is an attempt to understand the sediment movement in relation to beach dynamics, especially in the surf zone, along some part of Kerala coast and the response of the beaches to various forcing functions over different seasons

Design of an Edge -coupled dual -ring Split-ring resonator

Electric permittivity and magnetic permeability control electromagnetic wave propagation th rough materials. I n naturally occu rring materials, these are positive. Artificial materials exhi b iting negative material properties have been reported : they are referred to as metamaterials. This paper concentrates on a ring-type split-ring resonator (SRR) exhibiting negative magnetic permeability. The design and synthesis of the SRR using the genetic-algorithm approach is explained in detail. A user-friendly g raphical user i nterface (G U I ) for an SRR optim izer and estimator using MATLAB TM is also presented

Influence of substrate topography on the growth and magnetic properties of obliquely deposited amorphous nanocolumns of Fe–Ni

We investigated the influence of substrate surface roughness on the structural and magnetic properties of obliquely deposited amorphous nanocolumns of Fe–Ni. Experiments showed that the surface roughness of the substrate greatly determines the morphology of the columnar structures and this in turn has a profound influence on the magnetic properties. Nucleation of Fe–Ni nanocolumns on a smooth silicon substrate was at random, while that on a rough glass substrate was defined by the irregularities on the substrate surface. It has been found that magnetic interaction between the nanocolumns prepared on a silicon substrate was due to their small inter-column separation. Well separated nanocolumns on a glass substrate resulted in exchange isolated magnetic domains. The size, shape and the distribution of nanocolumns can be tailored by appropriately choosing the surface roughness of the substrate. This will find potential applications in thin film magnetism.