Development of ready-to-eat extruded fish based noodles in semi-rigid containers”

Fish and fishery products are having a unique place in global food market due to its unique taste and flavour; moreover, the presence of easily digestible proteins, lipids, vitamins and minerals make it a highly demanded food commodity.Fishery products constitute a major portion of international trade, which is a valuable source of foreign exchange to many developing countries.Several new technologies are emerging to produce various value added products from food; “extrusion technology” is one among them. Food extruder is a better choice for producing a wide variety of high value products at low volume because of its versatility. Extruded products are shelf-stable at ambient temperature. Extrusion cooking is used in the manufacture of food products such as ready-to-eat breakfast cereals, expanded snacks, pasta, fat-bread, soup and drink bases. The raw materialin the form of powder at ambient temperature is fed into extruder at a known feeding rate. The material first gets compacted and then softens and gelatinizes and/or melts to form a plasticized material, which flows downstream into extruder channel and the final quality of the end products depends on the characteristics of starch in the cereals and protein ingredient as affected by extrusion process. The advantages of extrusion process are the process is thermodynamically most efficient, high temperature short time enables destruction of bacteria and anti-nutritional factors, one step cooking process thereby minimizing wastage and destruction of fat hydrolyzing enzymes during extrusion process and enzymes associated with rancidity.

Nonlinear Dynamics of Semiconductor LasersControl and Synchronization of Chaos:

Nonlinear dynamics of laser systems has become an interesting area of research in recent times. Lasers are good examples of nonlinear dissipative systems showing many kinds of nonlinear phenomena such as chaos, multistability and quasiperiodicity. The study of these phenomena in lasers has fundamental scientific importance since the investigations on these effects reveal many interesting features of nonlinear effects in practical systems. Further, the understanding of the instabilities in lasers is helpful in detecting and controlling such effects. Chaos is one of the most interesting phenomena shown by nonlinear deterministic systems. It is found that, like many nonlinear dissipative systems, lasers also show chaos for certain ranges of parameters. Many investigations on laser chaos have been done in the last two decades. The earlier studies in this field were concentrated on the dynamical aspects of laser chaos. However, recent developments in this area mainly belong to the control and synchronization of chaos. A number of attempts have been reported in controlling or suppressing chaos in lasers since lasers are the practical systems aimed to operated in stable or periodic mode. On the other hand, laser chaos has been found to be applicable in high speed secure communication based on synchronization of chaos. Thus, chaos in laser systems has technological importance also. Semiconductor lasers are most applicable in the fields of optical communications among various kinds of laser due to many reasons such as their compactness, reliability modest cost and the opportunity of direct current modulation. They show chaos and other instabilities under various physical conditions such as direct modulation and optical or optoelectronic feedback. It is desirable for semiconductor lasers to have stable and regular operation. Thus, the understanding of chaos and other instabilities in semiconductor lasers and their xi control is highly important in photonics. We address the problem of controlling chaos produced by direct modulation of laser diodes. We consider the delay feedback control methods for this purpose and study their performance using numerical simulation. Besides the control of chaos, control of other nonlinear effects such as quasiperiodicity and bistability using delay feedback methods are also investigated. A number of secure communication schemes based on synchronization of chaos semiconductor lasers have been successfully demonstrated theoretically and experimentally. The current investigations in these field include the study of practical issues on the implementations of such encryption schemes. We theoretically study the issues such as channel delay, phase mismatch and frequency detuning on the synchronization of chaos in directly modulated laser diodes. It would be helpful for designing and implementing chaotic encryption schemes using synchronization of chaos in modulated semiconductor laser

Realization of a Scanning Photoacoustic Technique: Thermal properties of Bulk and Film Samples

Among the large number of photothcrmal techniques available, photoacoustics assumes a very significant place because of its essential simplicity and the variety of applications it finds in science and technology. The photoacoustic (PA) effect is the generation of an acoustic signal when a sample, kept inside an enclosed volume, is irradiated by an intensity modulated beam of radiation. The radiation absorbed by the sample is converted into thermal waves by nonradiative de-excitation processes. The propagating thermal waves cause a corresponding expansion and contraction of the gas medium surrounding the sample, which in tum can be detected as sound waves by a sensitive microphone. These sound waves have the same frequency as the initial modulation frequency of light. Lock-in detection method enables one to have a sufficiently high signal to noise ratio for the detected signal. The PA signal amplitude depends on the optical absorption coefficient of the sample and its thermal properties. The PA signal phase is a function of the thermal diffusivity of the sample.Measurement of the PA amplitude and phase enables one to get valuable information about the thermal and optical properties of the sample. Since the PA signal depends on the optical and thennal properties of the sample, their variation will get reflected in the PA signal. Therefore, if the PA signal is collected from various points on a sample surface it will give a profile of the variations in the optical/thennal properties across the sample surface. Since the optical and thermal properties are affected by the presence of defects, interfaces, change of material etc. these will get reflected in the PA signal. By varying the modulation frequency, we can get information about the subsurface features also. This is the basic principle of PA imaging or PA depth profiling. It is a quickly expanding field with potential applications in thin film technology, chemical engineering, biology, medical diagnosis etc. Since it is a non-destructive method, PA imaging has added advantages over some of the other imaging techniques. A major part of the work presented in this thesis is concemed with the development of a PA imaging setup that can be used to detect the presence of surface and subsmface defects in solid samples.Determination of thermal transport properties such as thermal diffusivity, effusivity, conductivity and heat capacity of materials is another application of photothennal effect. There are various methods, depending on the nature of the sample, to determine these properties. However, there are only a few methods developed to determine all these properties simultaneously. Even though a few techniques to determine the above thermal properties individually for a coating can be found in literature, no technique is available for the simultaneous measurement of these parameters for a coating. We have developed a scanning photoacoustic technique that can be used to determine all the above thermal transport properties simultaneously in the case of opaque coatings such as paints. Another work that we have presented in this thesis is the determination of thermal effusivity of many bulk solids by a scanning photoacoustic technique. This is one of the very few methods developed to determine thermal effiisivity directly.

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.

Some concepts and models usefulninthe analysis of discrete life time data

This thesis entitled Reliability Modelling and Analysis in Discrete time Some Concepts and Models Useful in the Analysis of discrete life time data.The present study consists of five chapters. In Chapter II we take up the derivation of some general results useful in reliability modelling that involves two component mixtures. Expression for the failure rate, mean residual life and second moment of residual life of the mixture distributions in terms of the corresponding quantities in the component distributions are investigated. Some applications of these results are also pointed out. The role of the geometric,Waring and negative hypergeometric distributions as models of life lengths in the discrete time domain has been discussed already. While describing various reliability characteristics, it was found that they can be often considered as a class. The applicability of these models in single populations naturally extends to the case of populations composed of sub-populations making mixtures of these distributions worth investigating. Accordingly the general properties, various reliability characteristics and characterizations of these models are discussed in chapter III. Inference of parameters in mixture distribution is usually a difficult problem because the mass function of the mixture is a linear function of the component masses that makes manipulation of the likelihood equations, leastsquare function etc and the resulting computations.very difficult. We show that one of our characterizations help in inferring the parameters of the geometric mixture without involving computational hazards. As mentioned in the review of results in the previous sections, partial moments were not studied extensively in literature especially in the case of discrete distributions. Chapters IV and V deal with descending and ascending partial factorial moments. Apart from studying their properties, we prove characterizations of distributions by functional forms of partial moments and establish recurrence relations between successive moments for some well known families. It is further demonstrated that partial moments are equally efficient and convenient compared to many of the conventional tools to resolve practical problems in reliability modelling and analysis. The study concludes by indicating some new problems that surfaced during the course of the present investigation which could be the subject for a future work in this area.

Paper industry in Kerala: An evaluation of labour absorption,capacity utilisation, and environmental pollution

Paper industry is one of the oldest and largest industries in Kerala. Despite the developments in the industry in terms of growth in output , value added and employment generation, many of the units face grave problems. Irrespective of the size of the plant, the problems of the industry are general in nature. The problems are galore in the supply, not the demand side. Amomg the problems, the important ones are: raw material scarcity, energy deficiency and obsolete technology. Further, the industry is subject to many controls by the Government — price control, product control and raw materials control — which result in the dwindling of profits and investments. Equally important are the reservations against the industry for polluting the environment byeffluent disposal on the one hand and affecting ecological balance by depleting the existing forest on the other. Apart from the large, medium and small pulp and paper mills, there are about 30 hand made paper units in Kerala which can be categorised as village and cottage industry. Almost all of these units began at the initiative and support of Khadi and Village Industries Commission. The primary purpose of these units is employment generation, and not profit making. Currently many of these units are in the red and many others are on the verge of closure. Therefore, a separate analysis of the growth performance, and problems and prospects of the hand made paper industry has also been attempted. It is analysed separately because of the very small size of the hand made paper units

Some aspects of history of Indian mathematics in 18th and early 19th century

This thesis is an attempt to throw light on the works of some Indian Mathematicians who wrote in Arabic or persian In the Introductory Chapter on outline of general history of Mathematics during the eighteenth Bnd nineteenth century has been sketched. During that period there were two streams of Mathematical activity. On one side many eminent scholers, who wrote in Sanskrit, .he l d the field as before without being much influenced by other sources. On the other side there were scholars whose writings were based on Arabic and Persian text but who occasionally drew upon other sources also.

Role of social pressure as a key contributor of materialism and related status consumption

“At resale stores I have seen brand new clothes with original price tag still hanging from the sleeve. Some children have so many toys that they stay frustrated, not knowing which one to pick up for their next amusement. Presumably sensible adults trade in perfectly good cars just to have something shinier and newer. Didn’t us once live productive normal lives, without all these gadgets” [Cunningham (2005)]. During late eighties, nearly forty four percent of the participants, who took part in a consumer survey conducted in the US, responded positively to the question “My closets are filled with still 2 unopened items” [Faber and O’Guinn (1988)]. Reading such excerpts does not greatly surprise us anymore; as such reports have become common now. For many people shopping has moved beyond something that caters to their needs and wants and has become a hobby [Cunningham (2005)], an activity that they engage in to satisfy their hedonistic or pleasure-seeking goals [Ramnathan and Menon(2006), O’Cass and McEween (2004), Faber and O’Guinn (1989)]. Others look at their new possession as something that fills a void in their lives [Belk (1985), Diener et al. (1993)].

Effectiveness Of Feature Detection Operators On The Performance Of Iris Biometric Recognition System

Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed systems, make it a good candidate to replace most of thesecurity systems around. By making use of the distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person. Identification of this person is possible by applying appropriate matching algorithm.In this paper, Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical analysis of different feature detection operators is performed, features extracted is encoded using Haar wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and False Reject Rate is 10%.

Changing Role of Academic Libraries in the E-learning Environment: Issues and Challenges

The development of computer and network technology is changing the education scenario and transforming the teaching and learning process from the traditional physical environment to the digital environment. It is now possible to access vast amount of information online and enable one to one communication without the confines of place or time. While E-learning and teaching is unlikely to replace face-to-face training and education it is becoming an additional delivery method, providing new learning opportunities to many users. It is also causing an impact on library services as the increased use of ICT and web based learning technologies have paved the way for providing new ICT based services and resources to the users. Online learning has a crucial role in user education, information literacy programmes and in training the library professionals. It can help students become active learners, and libraries will have to play a greater role in this process of transformation. The significance of libraries within an institution has improved due to the fact that academic libraries and information services are now responsible for e-learning within their organization.

Attribute reduction and missing value imputing with ANN: prediction of learning disabilities

Learning disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 10% of children enrolled in schools. There is no cure for learning disabilities and they are lifelong. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. Just as there are many different types of LDs, there are a variety of tests that may be done to pinpoint the problem The information gained from an evaluation is crucial for finding out how the parents and the school authorities can provide the best possible learning environment for child. This paper proposes a new approach in artificial neural network (ANN) for identifying LD in children at early stages so as to solve the problems faced by them and to get the benefits to the students, their parents and school authorities. In this study, we propose a closest fit algorithm data preprocessing with ANN classification to handle missing attribute values. This algorithm imputes the missing values in the preprocessing stage. Ignoring of missing attribute values is a common trend in all classifying algorithms. But, in this paper, we use an algorithm in a systematic approach for classification, which gives a satisfactory result in the prediction of LD. It acts as a tool for predicting the LD accurately, and good information of the child is made available to the concerned

Learning disability prediction tool using ANN and ANFIS

Learning Disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 15 % of children enrolled in schools. The prediction of LD is a vital and intricate job. The aim of this paper is to design an effective and powerful tool, using the two intelligent methods viz., Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System, for measuring the percentage of LD that affected in school-age children. In this study, we are proposing some soft computing methods in data preprocessing for improving the accuracy of the tool as well as the classifier. The data preprocessing is performed through Principal Component Analysis for attribute reduction and closest fit algorithm is used for imputing missing values. The main idea in developing the LD prediction tool is not only to predict the LD present in children but also to measure its percentage along with its class like low or minor or major. The system is implemented in Mathworks Software MatLab 7.10. The results obtained from this study have illustrated that the designed prediction system or tool is capable of measuring the LD effectively

A Reinforcement Learning Algorithm to Economic Dispatch Considering Transmission Losses

Reinforcement Learning (RL) refers to a class of learning algorithms in which learning system learns which action to take in different situations by using a scalar evaluation received from the environment on performing an action. RL has been successfully applied to many multi stage decision making problem (MDP) where in each stage the learning systems decides which action has to be taken. Economic Dispatch (ED) problem is an important scheduling problem in power systems, which decides the amount of generation to be allocated to each generating unit so that the total cost of generation is minimized without violating system constraints. In this paper we formulate economic dispatch problem as a multi stage decision making problem. In this paper, we also develop RL based algorithm to solve the ED problem. The performance of our algorithm is compared with other recent methods. The main advantage of our method is it can learn the schedule for all possible demands simultaneously.

Social Structural Determinants of Education among Tribes in Kerala

The study is focused on education of tribes particularly the problem of high dropout rate existing among the tribal students at school level. Scheduled Tribe is one of the marginalized communities experiencing high level of educational deprivation. The analysis of the study shows that the extent of deprivation existing among STs of Kerala is much higher compared to that of other communities. The present study covered tribes of three tribal predominant districts of Kerala such as Idukki, Palakkad and Wayanad. Out of the 35 tribal communities in the State, 17 of them are concentrated in these districts. Tribes concentrated in Idukki include Muthuvans, Malai Arayan, Uraly, Mannan and Hill Pulaya. The present study analyzed dropouts situation in tribal areas of Kerala by conducting Field Survey among dropout and non-dropout students at school level. High dropouts among STs persist due to many problems which are of structural in nature. Important problems faced by the tribal students that have been analyzed, this can be classified as economic, social, cultural and institutional. It is found that there exists high correlation between Income and expenditure of the family with the well-being of individuals. Significant economic factors are poverty and financial indebtedness of the family. Some of the common cultural factors of tribes are Nature of Habitation, Difference in Dialect and Medium of Instruction etc. Social factors analyzed in the study are illiteracy of parents, migration of family, family environment, motivation by parents, activities engaged in for helping the family and students’ lack of interest in studies. The analysis showed that all these factors except migration of the family, are affecting the education of tribal students. Apart from social, economic and cultural factors, there are a few institutional factors which will also influence the education of tribal students. Institutional factors analyzed in the study include students’ absenteeism, irregularity of teachers, attitude of non-tribal teachers and non-tribal students, infrastructure facilities and accessibility to school. The study found irregularity of students and accessibility to school as significant factors which determine the dropout of the students.

SHGs and Cooperatives in the Fishing Sector: An Inclusive Development Option for the Fisher folk of Kerala

The Kerala model of development mostly bypassed the fishing community, as the fishers form the main miserable groups with respect to many of the socio-economic and quality of life indicators. Modernization drive in the fishing sector paradoxically turns to marginalization drives as far as the traditional fishers in Kerala are concerned. Subsequent management and resource recuperation drives too seemed to be detrimental to the local fishing community. Though SHGs and cooperatives had helped in overcoming many of the maladies in most of the sectors in Kerala in terms of livelihood and employment in the 1980s, the fishing sector by that time had been moving ahead with mechanization and export euphoria and hence it bypassed the fishing sector. Though it has not helped the fishing sector in the initial stages, but because of necessity, it soon has become a vibrant livelihood and employment force in the coastal economy of Kerala. Initial success made it to link this with the governmental cooperative set up and soon SHGs and Cooperatives become reinforcing forces for the inclusive development of the real fishers.The fisheries sector in Kerala has undergone drastic changes with the advent of globalised economy. The traditional fisher folk are one of the most marginalized communities in the state and are left out of the overall development process mainly due to the marginalization of this community both in the sea and in the market due to modernization and mechanization of the sector. Mechanization opened up the sector a great deal as it began to attract people belonging to non-fishing community as moneylenders, boat owners, employers and middle men which often resulted in conflicts between traditional and mechanized fishermen. These factors, together with resource depletion resulted in the backwardness experienced by the traditional fishermen compared to other communities who were reaping the benefits of the overall development scenario.The studies detailing the activities and achievements of fisher folks via Self Help Groups (SHGs) and the cooperative movement in coastal Kerala are scant. The SHGs through cooperatives have been effective in livelihood security, poverty alleviation and inclusive development of the fisher folk (Rajasenan and Rajeev, 2012). The SHGs have a greater role to play as estimated fall in demand for marine products in international markets, which may result in reduction of employment opportunities in fish processing, peeling, etc. Also, technological advancement has made them unskilled to work in this sector making them outliers in the overall development process resulting in poor quality of physical and social infrastructure. Hence, it is all the more important to derive a strategy and best practice methods for the effective functioning of these SHGs so that the