Abstract: | Recent studies have established a fimctional correlation of serotonergic and adrenergic function in the brain regions with insulin secretion in diabetic rats (Vahabzadeh et al., 1995). Administration of 5-HT”. agonist 8-OH-DPAT to conscious rats caused an increase in blood glucose level. This increase in blood glucose is due to inhibition of insulin secretion by increased circulating EPI (Chaouloff et al., 1990a; Chaouloff et al., 1990d; Chaoulo1T& Jeanrenaud, 1987). The increase in EPI is brought about by increased sympathetic stimulation. This increase can lead to increased sympatho-medullary stimulation thereby inhibiting insulin release (Bauhelal & Mir, 1993, Bauhelal & Mir, 1990a; Chaouloffet al., 1990d). Also, studies have shown that Gi protein in the liver has been decreased in diabetes which will increase gluconeogenesis and glycogenolysis thereby causing hyperglycaemia (Pennington, 1987). Serotonergic control is suggested to exert different effects on insulin secretion according to the activation of different receptor subclasses (Pontiroli et al., 1975). In addition to this mechanism, the secretion of insulin is dependent on the turnover ratio of endogenous 5-hydroxy tryptophan (5-HTP) to 5-HT in the pancreatic islets (Jance er al., 1980). The reports so far stated does not explain the complete mechanism and the subclass of 5-HT receptors whose expression regulate insulin secretion in a diabetic state. Also, there is no report of a direct regulation of insulin secretion by 5-HT from the pancreatic islets even though there are reports stating that the pancreatic islets is a rich source of 5-HT (Bird et al., 1980). Therefore, in the present study the mechanism by which 5-HT and its receptors regulate insulin secretion from pancreatic [3-cells was investigated. Our results led to the following hypotheses by which 5-HT and its receptors regulate the insulin secretion. |
Description: | Department of Biotechnology, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3513 |
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Dyuthi-T1486.pdf | (9.126Mb) |
Abstract: | The present study deals with the short isora fibre reinforced natural rubber composites. In recent years there has been a tremendous advancement in the field of science and technology of short fibre reinforced polymer composites. The low density, high strength, high stiffness to weight ratio, excellent durability and design flexibility are the primary reasons for their use in many diversified fields such as air crafts, automobiles, marine industry etc. Compared to the various natural and synthetic fibres used as reinforcement for elastomer composites isora fibre is superior in many aspects. `Isora' is a natural lignocellulosic fibre which is easily available in South India especially in Kerala. The fibre is separated from the bark of the Helicteres isora plant by retting process. This fibre has excellent mechanical properties and is easily amenable to physical and chemical modifications. The study shows that composites with poor interfacial bonding tend to dissipate more energy than that with to interfacial bonding. The mechanical loss also can be related to interfacial bonding. The effect of chemical treatment of isora fibre on damping was also studied. Both in the low and high temperature region which indicates that this composite posseses low damping and hence good interfacial bonding characteristics. Hence these composites are better candidates for high damping applications. Composites with longitudinally oriented fibres showed high storage modulus than transversely oriented ones due to the effective stress transfer between fibre and matrix. |
URI: | http://dyuthi.cusat.ac.in/purl/928 |
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Dyuthi-T0146.pdf | (9.293Mb) |
Abstract: | The thesis describes studies on development of short Nylon-6 fibre composites based on rubber-toughened polystyrene (PS). Toughening was done using natural rubber (NR), styrene-butadiene rubber (SBR) and whole tyre reclaim (WTR). The composites were prepared by melt mixing in an internal mixer at 170 oC. It was found that the optimum blend ratio was 85/15 for PS/NR, 90/10 for PS/SBR and 90/22 for PS/WTR blends. The effect of dynamic vulcanisation on 85/15 PS/NR and 90/10 PS/SBR blends using dicumyl peroxide (DCP) at various concentrations were also studied. The dynamic crosslinking improved the tensile properties, flexural properties, impact strength and dynamic mechanical properties of both the blends. The effect of unmodified and resorcinol formaldehyde latex (RFL)-coated short Nylon-6 fibres on the mechanical properties, morphology and dynamic mechanical properties of 85/15 PS/NR, 90/10 PS/SBR and 90/22 PS/WTR blends were studied. Fibre loading was varied from 0 to 3 wt.%. For 85/15 PS/NR blend, there was a significant enhancement in tensile properties, flexural properties and impact strength with 1 wt.% of both unmodified and RFL-coated fibres. Dynamic mechanical analysis revealed that the storage modulus at room temperature was maximum at 1 wt.% fiber loading for both composites. The surface functionality of the fiber was improved by giving alkali treatment. Maleic anhydride-grafted-polystyrene (MA-g-PS) was prepared and used as a compatibiliser. The effect of MA-g-PS on the composites was investigated with respect to mechanical properties, morphology and dynamic mechanical properties. The compatibiliser loading was varied from 0 to 2 wt.%. The properties were enhanced significantly in the case of treated and untreated fibre composites at a compatibiliser loading of 0.75 wt.%. SEM analysis confirmed better bonding between the fibre and the matrix. Dynamic mechanical studies showed that the storage modulus at room temperature improved for treated fibre composites in the presence of compatibiliser. In the case of 90/10 PS/SBR composites, the addition of short Nylon-6 fibres at 1 wt.% loading improved the tensile modulus, flexural properties and impact strength while the tensile strength was marginally reduced. The surface treated fibers along with compatibiliser at 0.5 wt.% improved the tensile properties, flexural properties and impact strength. DMA reveale that the storage modulus at room temperature was better for composites containing untreated fibre and the compatibiliser. In the case of 90/22 PS/WTR blends, 1 wt.% unmodified fibre and 0.5 wt.% RFL-coated fibres improved tensile modulus, flexural properties and impact strength. Tensile strength was improved marginally. The surface treatment of Nylon fibre and the addition of compatibiliser at 0.5 wt.% enhanced the tensile properties, flexural properties and impact strength. The dynamic mechanical analysis showed that the storage modulus at room temperature was better for untreated fibre composites in conjunction with the compatibiliser. The thermal stability of PS/NR was studied by TGA. Thermal stability of the blends improved with dynamic vulcanisation and with the incorporation of RFL-coated Nylon fibres. The untreated and partially hydrolyzed fibre composites in conjunction with the compatibiliser enhanced the thermal stability. Kinetic studies showed that the degradation of the blends and the composites followed first order kinetics. |
Description: | Department of Polymer Science and Rubber Technology, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3063 |
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Dyuthi-T1037.pdf | (8.227Mb) |
Abstract: | The brain with its highly complex structure made up of simple units,imterconnected information pathways and specialized functions has always been an object of mystery and sceintific fascination for physiologists,neuroscientists and lately to mathematicians and physicists. The stream of biophysicists are engaged in building the bridge between the biological and physical sciences guided by a conviction that natural scenarios that appear extraordinarily complex may be tackled by application of principles from the realm of physical sciences. In a similar vein, this report aims to describe how nerve cells execute transmission of signals ,how these are put together and how out of this integration higher functions emerge and get reflected in the electrical signals that are produced in the brain.Viewing the E E G Signal through the looking glass of nonlinear theory, the dynamics of the underlying complex system-the brain ,is inferred and significant implications of the findings are explored. |
Description: | International School of Photonics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2242 |
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Dyuthi-T0570.pdf | (11.01Mb) |
Abstract: | Post-transcriptional gene silencing by RNA interference is mediated by small interfering RNA called siRNA. This gene silencing mechanism can be exploited therapeutically to a wide variety of disease-associated targets, especially in AIDS, neurodegenerative diseases, cholesterol and cancer on mice with the hope of extending these approaches to treat humans. Over the recent past, a significant amount of work has been undertaken to understand the gene silencing mediated by exogenous siRNA. The design of efficient exogenous siRNA sequences is challenging because of many issues related to siRNA. While designing efficient siRNA, target mRNAs must be selected such that their corresponding siRNAs are likely to be efficient against that target and unlikely to accidentally silence other transcripts due to sequence similarity. So before doing gene silencing by siRNAs, it is essential to analyze their off-target effects in addition to their inhibition efficiency against a particular target. Hence designing exogenous siRNA with good knock-down efficiency and target specificity is an area of concern to be addressed. Some methods have been developed already by considering both inhibition efficiency and off-target possibility of siRNA against agene. Out of these methods, only a few have achieved good inhibition efficiency, specificity and sensitivity. The main focus of this thesis is to develop computational methods to optimize the efficiency of siRNA in terms of “inhibition capacity and off-target possibility” against target mRNAs with improved efficacy, which may be useful in the area of gene silencing and drug design for tumor development. This study aims to investigate the currently available siRNA prediction approaches and to devise a better computational approach to tackle the problem of siRNA efficacy by inhibition capacity and off-target possibility. The strength and limitations of the available approaches are investigated and taken into consideration for making improved solution. Thus the approaches proposed in this study extend some of the good scoring previous state of the art techniques by incorporating machine learning and statistical approaches and thermodynamic features like whole stacking energy to improve the prediction accuracy, inhibition efficiency, sensitivity and specificity. Here, we propose one Support Vector Machine (SVM) model, and two Artificial Neural Network (ANN) models for siRNA efficiency prediction. In SVM model, the classification property is used to classify whether the siRNA is efficient or inefficient in silencing a target gene. The first ANNmodel, named siRNA Designer, is used for optimizing the inhibition efficiency of siRNA against target genes. The second ANN model, named Optimized siRNA Designer, OpsiD, produces efficient siRNAs with high inhibition efficiency to degrade target genes with improved sensitivity-specificity, and identifies the off-target knockdown possibility of siRNA against non-target genes. The models are trained and tested against a large data set of siRNA sequences. The validations are conducted using Pearson Correlation Coefficient, Mathews Correlation Coefficient, Receiver Operating Characteristic analysis, Accuracy of prediction, Sensitivity and Specificity. It is found that the approach, OpsiD, is capable of predicting the inhibition capacity of siRNA against a target mRNA with improved results over the state of the art techniques. Also we are able to understand the influence of whole stacking energy on efficiency of siRNA. The model is further improved by including the ability to identify the “off-target possibility” of predicted siRNA on non-target genes. Thus the proposed model, OpsiD, can predict optimized siRNA by considering both “inhibition efficiency on target genes and off-target possibility on non-target genes”, with improved inhibition efficiency, specificity and sensitivity. Since we have taken efforts to optimize the siRNA efficacy in terms of “inhibition efficiency and offtarget possibility”, we hope that the risk of “off-target effect” while doing gene silencing in various bioinformatics fields can be overcome to a great extent. These findings may provide new insights into cancer diagnosis, prognosis and therapy by gene silencing. The approach may be found useful for designing exogenous siRNA for therapeutic applications and gene silencing techniques in different areas of bioinformatics. |
URI: | http://dyuthi.cusat.ac.in/purl/5039 |
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Dyuthi-T2104.pdf | (5.751Mb) |
Abstract: | The thesis introduced the octree and addressed the complete nature of problems encountered, while building and imaging system based on octrees. An efficient Bottom-up recursive algorithm and its iterative counterpart for the raster to octree conversion of CAT scan slices, to improve the speed of generating the octree from the slices, the possibility of utilizing the inherent parallesism in the conversion programme is explored in this thesis. The octree node, which stores the volume information in cube often stores the average density information could lead to “patchy”distribution of density during the image reconstruction. In an attempt to alleviate this problem and explored the possibility of using VQ to represent the imformation contained within a cube. Considering the ease of accommodating the process of compressing the information during the generation of octrees from CAT scan slices, proposed use of wavelet transforms to generate the compressed information in a cube. The modified algorithm for generating octrees from the slices is shown to accommodate the eavelet compression easily. Rendering the stored information in the form of octree is a complex task, necessarily because of the requirement to display the volumetric information. The reys traced from each cube in the octree, sum up the density en-route, accounting for the opacities and transparencies produced due to variations in density. |
URI: | http://dyuthi.cusat.ac.in/purl/977 |
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Dyuthi-T0151.pdf | (4.667Mb) |
Abstract: | One of the fastest expanding areas of computer exploitation is in embedded systems, whose prime function is not that of computing, but which nevertheless require information processing in order to carry out their prime function. Advances in hardware technology have made multi microprocessor systems a viable alternative to uniprocessor systems in many embedded application areas. This thesis reports the results of investigations carried out on multi microprocessors oriented towards embedded applications, with a view to enhancing throughput and reliability. An ideal controller for multiprocessor operation is developed which would smoothen sharing of routines and enable more powerful and efficient code I data interchange. Results of performance evaluation are appended.A typical application scenario is presented, which calls for classifying tasks based on characteristic features that were identified. The different classes are introduced along with a partitioned storage scheme. Theoretical analysis is also given. A review of schemes available for reducing disc access time is carried out and a new scheme presented. This is found to speed up data base transactions in embedded systems. The significance of software maintenance and adaptation in such applications is highlighted. A novel scheme of prov1d1ng a maintenance folio to system firmware is presented, alongwith experimental results. Processing reliability can be enhanced if facility exists to check if a particular instruction in a stream is appropriate. Likelihood of occurrence of a particular instruction would be more prudent if number of instructions in the set is less. A new organisation is derived to form the basement for further work. Some early results that would help steer the course of the work are presented. |
Description: | Department of Electronics,Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2195 |
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Dyuthi-T0554.pdf | (4.004Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5239 |
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Dyuthi T-2275.pdf | (3.929Mb) |
Abstract: | The aim of the thesis was to design and develop spatially adaptive denoising techniques with edge and feature preservation, for images corrupted with additive white Gaussian noise and SAR images affected with speckle noise. Image denoising is a well researched topic. It has found multifaceted applications in our day to day life. Image denoising based on multi resolution analysis using wavelet transform has received considerable attention in recent years. The directionlet based denoising schemes presented in this thesis are effective in preserving the image specific features like edges and contours in denoising. Scope of this research is still open in areas like further optimization in terms of speed and extension of the techniques to other related areas like colour and video image denoising. Such studies would further augment the practical use of these techniques. |
URI: | http://dyuthi.cusat.ac.in/purl/4947 |
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Dyuthi-T2020.pdf | (7.897Mb) |
Abstract: | Motivation for Speaker recognition work is presented in the first part of the thesis. An exhaustive survey of past work in this field is also presented. A low cost system not including complex computation has been chosen for implementation. Towards achieving this a PC based system is designed and developed. A front end analog to digital convertor (12 bit) is built and interfaced to a PC. Software to control the ADC and to perform various analytical functions including feature vector evaluation is developed. It is shown that a fixed set of phrases incorporating evenly balanced phonemes is aptly suited for the speaker recognition work at hand. A set of phrases are chosen for recognition. Two new methods are adopted for the feature evaluation. Some new measurements involving a symmetry check method for pitch period detection and ACE‘ are used as featured. Arguments are provided to show the need for a new model for speech production. Starting from heuristic, a knowledge based (KB) speech production model is presented. In this model, a KB provides impulses to a voice producing mechanism and constant correction is applied via a feedback path. It is this correction that differs from speaker to speaker. Methods of defining measurable parameters for use as features are described. Algorithms for speaker recognition are developed and implemented. Two methods are presented. The first is based on the model postulated. Here the entropy on the utterance of a phoneme is evaluated. The transitions of voiced regions are used as speaker dependent features. The second method presented uses features found in other works, but evaluated differently. A knock—out scheme is used to provide the weightage values for the selection of features. Results of implementation are presented which show on an average of 80% recognition. It is also shown that if there are long gaps between sessions, the performance deteriorates and is speaker dependent. Cross recognition percentages are also presented and this in the worst case rises to 30% while the best case is 0%. Suggestions for further work are given in the concluding chapter. |
Description: | Department of Electronics, Cochin University of Science And Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3721 |
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Dyuthi-T1677.pdf | (2.949Mb) |
Abstract: | The spectral and nonlinear optical characteristics of nano ZnO and its composites are investigated. The fluorescence behaviour of nano colloids of ZnO has been studied as a function of the excitation wavelength and there is a red shift in emission peak with excitation wavelength. Apart from the observation of the reported ultra violet and green emissions, our results reveal that additional blue emissions at 420 nm and 490 nm are developed with increasing particle size. Systematic studies on nano ZnO have indicated the presence of luminescence due to excitonic emissions when excited with 255 nm as well as significant contribution from surface defect states when excited with 325 nm. In the weak confinement regime, the third-order optical susceptibility χ(3) increases with increasing particle size (R) and annealing temperature (T) and a R2 and T2.5 dependence of χ(3) is obtained for nano ZnO. ZnO nanocolloids exhibit induced absorption whereas the self assembled films of ZnO exhibit saturable absorption due to saturation of linear absorption of ZnO defect states and electronic effects. ZnO nanocomposites exhibit negative nonlinear index of refraction which can be attributed to two photon absorption followed by weak free carrier absorption. The increase of the third-order nonlinearity in the composites can be attributed to the enhancement of exciton oscillator strength. The nonlinear response of ZnO nanocomposites is wavelength dependent and switching from induced absorption to saturable absorption has been observed at resonant wavelengths. Such a change-over is related to the interplay of plasmon/exciton band bleach and optical limiting mechanisms. This study is important in identifying the spectral range and the composition over which the nonlinear material acts as an optical limiter. ZnO based nanocomposites are potential materials for enhanced and tunable light emission and for the development of nonlinear optical devices with a relatively small optical limiting threshold. |
URI: | http://dyuthi.cusat.ac.in/jspui/handle/dyuthi/1674 |
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Dyuthi-T0546.pdf | (2.426Mb) |
Abstract: | Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects. |
Description: | International School of Photonics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2665 |
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Dyuthi-T0847.pdf | (4.954Mb) |
Abstract: | This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder |
Description: | Department of Electronics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3396 |
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Dyuthi-T1373.pdf | (4.336Mb) |
URI: | http://dyuthi.cusat.ac.in/purl/5232 |
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Dyuthi T-2267.pdf | (9.710Mb) |
Abstract: | 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. |
Description: | Department of Computer Applications, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3069 |
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Dyuthi-T1043.pdf | (3.015Mb) |
Abstract: | Electromagnetic tomography has been applied to problems in nondestructive evolution, ground-penetrating radar, synthetic aperture radar, target identification, electrical well logging, medical imaging etc. The problem of electromagnetic tomography involves the estimation of cross sectional distribution dielectric permittivity, conductivity etc based on measurement of the scattered fields. The inverse scattering problem of electromagnetic imaging is highly non linear and ill posed, and is liable to get trapped in local minima. The iterative solution techniques employed for computing the inverse scattering problem of electromagnetic imaging are highly computation intensive. Thus the solution to electromagnetic imaging problem is beset with convergence and computational issues. The attempt of this thesis is to develop methods suitable for improving the convergence and reduce the total computations for tomographic imaging of two dimensional dielectric cylinders illuminated by TM polarized waves, where the scattering problem is defmed using scalar equations. A multi resolution frequency hopping approach was proposed as opposed to the conventional frequency hopping approach employed to image large inhomogeneous scatterers. The strategy was tested on both synthetic and experimental data and gave results that were better localized and also accelerated the iterative procedure employed for the imaging. A Degree of Symmetry formulation was introduced to locate the scatterer in the investigation domain when the scatterer cross section was circular. The investigation domain could thus be reduced which reduced the degrees of freedom of the inverse scattering process. Thus the entire measured scattered data was available for the optimization of fewer numbers of pixels. This resulted in better and more robust reconstructions of the scatterer cross sectional profile. The Degree of Symmetry formulation could also be applied to the practical problem of limited angle tomography, as in the case of a buried pipeline, where the ill posedness is much larger. The formulation was also tested using experimental data generated from an experimental setup that was designed. The experimental results confirmed the practical applicability of the formulation. |
Description: | Department of Electronics, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2546 |
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Dyuthi-T0690.pdf | (8.779Mb) |
Abstract: | Hat Stiffened Plates are used in composite ships and are gaining popularity in metallic ship construction due to its high strength-to-weight ratio. Light weight structures will result in greater payload, higher speeds, reduced fuel consumption and environmental emissions. Numerical Investigations have been carried out using the commercial Finite Element software ANSYS 12 to substantiate the high strength-to-weight ratio of Hat Stiffened Plates over other open section stiffeners which are commonly used in ship building. Analysis of stiffened plate has always been a matter of concern for the structural engineers since it has been rather difficult to quantify the actual load sharing between stiffeners and plating. Finite Element Method has been accepted as an efficient tool for the analysis of stiffened plated structure. Best results using the Finite Element Method for the analysis of thin plated structures are obtained when both the stiffeners and the plate are modeled using thin plate elements having six degrees of freedom per node. However, one serious problem encountered with this design and analysis process is that the generation of the finite element models for a complex configuration is time consuming and laborious. In order to overcome these difficulties two different methods viz., Orthotropic Plate Model and Superelement for Hat Stiffened Plate have been suggested in the present work. In the Orthotropic Plate Model geometric orthotropy is converted to material orthotropy i.e., the stiffeners are smeared and they vanish from the field of analysis and the structure can be analysed using any commercial Finite Element software which has orthotropic elements in its element library. The Orthotropic Plate Model developed has predicted deflection, stress and linear buckling load with sufficiently good accuracy in the case of all four edges simply supported boundary condition. Whereas, in the case of two edges fixed and other two edges simply supported boundary condition even though the stress has been predicted with good accuracy there has been large variation in the deflection predicted. This variation in the deflection predicted is because, for the Orthotropic Plate Model the rigidity is uniform throughout the plate whereas in the actual Hat Stiffened Plate the rigidity along the line of attachment of the stiffeners to the plate is large as compared to the unsupported portion of the plate. The Superelement technique is a method of treating a portion of the structure as if it were a single element even though it is made up of many individual elements. The Superelement has predicted the deflection and in-plane stress of Hat Stiffened Plate with sufficiently good accuracy for different boundary conditions. Formulation of Superelement for composite Hat Stiffened Plate has also been presented in the thesis. The capability of Orthotropic Plate Model and Superelement to handle typical boundary conditions and characteristic loads in a ship structure has been demonstrated through numerical investigations. |
Description: | Study about Hat Stiffened Plate |
URI: | http://dyuthi.cusat.ac.in/purl/5038 |
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Dyuthi-T2103 .pdf | (2.669Mb) |
Abstract: | Developments in laser technology over the past few years have made it possible to do experiments with focused intensities of IO"-102' Wcm'z. Short-pulse high-intensity lasers are able to accelerate protons and heavier ions to multi-MeV energies during their interaction with solid targets, gas jets and clusters. When such a laser radiation is focused at the intensity above 10” Wcm'2, local electric field strength will be almost equivalent to that within an atom. Hence, new nonlinear optical phenomena will be expected in the field of light matter interaction. Most of the research in the material interaction using high power lasers, especially related to plasma interaction, has been directed to the short pulse x-ray generation- Nanosecond laser interactions with solid targets also generate plasmas which emit radiation mainly in the optical region, the understanding of which is far from satisfactory. This thesis deals with a detailed study of some of the dynamical processes in plasmas generated by nanosecond and femtosecond lasers |
Description: | lntemational School of Photonics Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3853 |
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Dyuthi-T1780.pdf | (2.323Mb) |
Abstract: | Internet today has become a vital part of day to day life, owing to the revolutionary changes it has brought about in various fields. Dependence on the Internet as an information highway and knowledge bank is exponentially increasing so that a going back is beyond imagination. Transfer of critical information is also being carried out through the Internet. This widespread use of the Internet coupled with the tremendous growth in e-commerce and m-commerce has created a vital need for infonnation security.Internet has also become an active field of crackers and intruders. The whole development in this area can become null and void if fool-proof security of the data is not ensured without a chance of being adulterated. It is, hence a challenge before the professional community to develop systems to ensure security of the data sent through the Internet.Stream ciphers, hash functions and message authentication codes play vital roles in providing security services like confidentiality, integrity and authentication of the data sent through the Internet. There are several ·such popular and dependable techniques, which have been in use widely, for quite a long time. This long term exposure makes them vulnerable to successful or near successful attempts for attacks. Hence it is the need of the hour to develop new algorithms with better security.Hence studies were conducted on various types of algorithms being used in this area. Focus was given to identify the properties imparting security at this stage. By making use of a perception derived from these studies, new algorithms were designed. Performances of these algorithms were then studied followed by necessary modifications to yield an improved system consisting of a new stream cipher algorithm MAJE4, a new hash code JERIM- 320 and a new message authentication code MACJER-320. Detailed analysis and comparison with the existing popular schemes were also carried out to establish the security levels.The Secure Socket Layer (SSL) I Transport Layer Security (TLS) protocol is one of the most widely used security protocols in Internet. The cryptographic algorithms RC4 and HMAC have been in use for achieving security services like confidentiality and authentication in the SSL I TLS. But recent attacks on RC4 and HMAC have raised questions about the reliability of these algorithms. Hence MAJE4 and MACJER-320 have been proposed as substitutes for them. Detailed studies on the performance of these new algorithms were carried out; it has been observed that they are dependable alternatives. |
Description: | Department of Computer Science, Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/2689 |
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Dyuthi-T0741.pdf | (3.003Mb) |
Abstract: | This thesis is essentially concerned with a study of the recovery of pungency-free colour matter from capsicum spice of Indian origin. A spice oleoresin may be defined as the total soluble extract of the spice in a specific solvent and embraces all the active components that contribute to aroma, taste and related sensory factors associated with the spice, together with varying amounts of pigments, plant waxes, resins and fixed oils. Whereas, in general, oleoresins are coveted for their flavour qualities, in some cases, the pigments present therein play a vital role in food technology Of these, capsicum oleoresin is the most outstanding, since it contributes both colour and flavour principles. |
Description: | Department of Polymer Science and Rubber Technology Cochin University of Science and Technology |
URI: | http://dyuthi.cusat.ac.in/purl/3450 |
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Dyuthi-T1435.pdf | (1.060Mb) |
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