| Abstract: | Natural rubber latex, an aqueous colloidal dispersion of polyisoprene is widely used in production of gloves, catherers, rubber bands etc. The natural rubber latex content present in products such as gloves causes allergic problems. Of the different types of allergies reported, latex is known to produce Type I and Type IV allergies. Type I is called immediate hypersensitivity and type IV is called delayed hypersensitivity. It has been reported that some of the proteins present in the latex are mainly responsible for the allergic reactions type I. Significant reduction in the allergic response (type I) of natural rubber latex can be achieved by the reduction in its protein content, however out of the total proteins present in the latex or latex film only a fraction is extractable. The major techniques employed to reduce protein content of latex include leaching, autoclaving, chlorination, use of proteolytic enzymes and use of non ionic surfactants. Sulphur vulcanization of dipped products is responsible for Type IV allergy. N-nitrosamine, a carcinogenic substance is produced as a result of sulphur vulcanization. Radiation vulcanization can be used as an alternative for sulphur vulcanization. The current research deals with techniques to reduce the allergy associated with latex products. To reduce the type I allergy, low protein latex is developed using polyethylene glycol, a non- ionic surfactant. The present study employs radiation vulcanization to eliminate type IV allergy. The effect of different cure systems and fillers on the properties of low protein latex is also investigated as a part of the study. |
| URI: | http://dyuthi.cusat.ac.in/purl/5091 |
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| Dyuthi-T2157.pdf.pdf | (8.640Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5233 |
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| Dyuthi T-2268.pdf | (4.339Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5065 |
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| Dyuthi-T2131.pdf | (83.01Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5185 |
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| Dyuthi T-2220.pdf | (9.779Mb) |
| Abstract: | Organic-inorganic nanocomposites combine unique properties of both the constituents in one material. Among this group of materials, clay based as well as ZnO, TiO2 nanocomposites have been found to have diverse applications. Optoelectronic devices require polymerinorganic systems to meet certain desired properties. Dielectric properties of conventional polymers like poly(ethylene-co-vinyl acetate) (EVA) and polystyrene (PS) may also be tailor tuned with the incorporation of inorganic fillers in very small amounts. Electrical conductivity and surface resistivity of polymer matrices are found to improve with inorganic nanofillers. II-VI semiconductors and their nano materials have attracted material scientists because of their unique optical properties of photoluminescence, UV photodetection and light induced conductivity. Cadmium selenide (CdSe), zinc selenide (ZnSe) and zinc oxide (ZnO) are some of the most promising members of the IIVI semiconductor family, used in light-emitting diodes, nanosensors, non-linear optical (NLO) absorption etc. EVA and PS materials were selected as the matrices in the present study because they are commercially used polymers and have not been the subject of research for opto-electronic properties with semiconductor nanomaterials |
| URI: | http://dyuthi.cusat.ac.in/purl/5111 |
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| Dyuthi-T 2176.pdf | (17.16Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5205 |
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| Dyuthi T-2240.pdf | (8.622Mb) |
| Abstract: | The semiconductor industry's urge towards faster, smaller and cheaper integrated circuits has lead the industry to smaller node devices. The integrated circuits that are now under volume production belong to 22 nm and 14 nm technology nodes. In 2007 the 45 nm technology came with the revolutionary high- /metal gate structure. 22 nm technology utilizes fully depleted tri-gate transistor structure. The 14 nm technology is a continuation of the 22 nm technology. Intel is using second generation tri-gate technology in 14 nm devices. After 14 nm, the semiconductor industry is expected to continue the scaling with 10 nm devices followed by 7 nm. Recently, IBM has announced successful production of 7 nm node test chips. This is the fashion how nanoelectronics industry is proceeding with its scaling trend. For the present node of technologies selective deposition and selective removal of the materials are required. Atomic layer deposition and the atomic layer etching are the respective techniques used for selective deposition and selective removal. Atomic layer deposition still remains as a futuristic manufacturing approach that deposits materials and lms in exact places. In addition to the nano/microelectronics industry, ALD is also widening its application areas and acceptance. The usage of ALD equipments in industry exhibits a diversi cation trend. With this trend, large area, batch processing, particle ALD and plasma enhanced like ALD equipments are becoming prominent in industrial applications. In this work, the development of an atomic layer deposition tool with microwave plasma capability is described, which is a ordable even for lightly funded research labs. |
| URI: | http://dyuthi.cusat.ac.in/purl/5101 |
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| Dyuthi-T 2167 .pdf | (21.87Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5192 |
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| Dyuthi T-2227.pdf | (2.863Mb) |
| Abstract: | Semiconductor lasers with different types of feedback schemes have been an active research area for many years. Feedback can induce complex phenomena in semiconductor lasers and their investigations often helped to understand the inner mechanisms of the laser. The possibility of using high dimensional chaos induced in semiconductor lasers by delayed feedback, for secure communication systems was a major motivation for intense research in the subject. Recently these systems also served as a testbed for general investigations on delay dynamical systems. The present study focuses on the aspects of the dynamical behavior of semiconductor lasers which are induced by delay feedback. |
| URI: | http://dyuthi.cusat.ac.in/purl/5147 |
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| Dyuthi-T2181.pdf | (8.910Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5188 |
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| Dyuthi T-2223.pdf | (4.427Mb) |
| Abstract: | We live in an Information age, which is marked by the onset of digital revolution during or after the latter half of the 20th century. In this era, we saw sweeping changes in digital computing and communication technology. We largely depend on electronics and photonics for hardware requirements to aid this technology. With the assistance of modern technology, electronic devices have become an indispensable tool in our everyday life. Inorganic semiconductor materials like silicon and gallium arsenide have been exploited for the on-growing demands of digital revolution. Fifty years of continuous research and technological advancements have pushed these materials to their theoretical efficiency limit. On the other hand, the rapid advancement in technology has created a huge electronic waste which pose a threat to the environment. The scarcity of inorganic materials such as gallium and indium is an alarming factor and it is estimated that these will run out completely in the next 20 years. The availability of new suitable materials is crucial for the development of semiconductor technology. With much promise of delivering low-cost and energy efficient materials, organic semiconductors such as conjugated polymers and small molecules have opened up new avenues for research. Despite the intense effort by scientists and researchers, the performance and stability of organic devices have taken a back seat. Therefore an immediate large-scale replacement of inorganic components by organic counterparts are not foreseen in the near future. Although research is underway to improve the performance of organic materials, it is important to constantly search for new materials.Nature is a big treasure-trove of successfully conducted experiments by natural selection. Inspired by its apparent simplicity and actual complexity, researchers look out for natural materials or synthetic materials mimicked from natural models, systems or elements. Bio-inspired photonics use natural design as their inspiration to solve human problems and channel these solutions in new directions. It is promising that natural and nature-inspired materials can achieve the ambitious goal of ‘green’ technology for sustainable future. |
| URI: | http://dyuthi.cusat.ac.in/purl/5156 |
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| Dyuthi-T2190.pdf | (8.356Mb) |
| Abstract: | In this century, computers have become an inseparable part of human life. Human beings entrust them with day-to-day activities and as well as highly sensitive data such as credit card information. Therefore, it is highly essential to ensure the proper working of the software before it is handed over to the users. Simple errors in the software may cause billions of dollar loss or even cause harm to human life. Therefore, the software needs to be dependable and reliable. Software testing is one of the most important methods to assure an error free software. This thesis work is centered on software testing. One of the major concerns in today’s practical software testing is the size of the source code which the testers have to deal with. Simple and effective testing methods that can handle the issue of source code length are highly essential. As the length of the program increases, testing activities like test case generation and test execution becomes more complicated. From the literature review it was evident that most of the existing methods for software testing did not address the problem of source code size during testing. Considering these scenarios, the work presented in this thesis tries to handle these challenges in practical software testing so as to make testing easier. With this aim, we have proposed a forward slicing based framework which helps to identify the statements of relevance in a software. Program slicing is used in several fields like program comprehension, debugging, software maintenance, program cohesion, refactoring and reverse engineering. Anyhow, the works that explicitly demonstrate how program slicing may be applied in software testing is extremely rare. In this thesis, we have clearly demonstrated how to perform software testing and trace dependencies in the source code using forward slicing. A formal representation of forward slicing is also presented in this work. As an extension to our forward slicing framework, we have also introduced the concept of partitioned forward slices and partial slices which helps the testers to focus on statements of interest. Partitioned forward slices helps to handle the large size of forward slices whereas partial slices identifies statements of interest with respect to output variables. The research finding finally concludes that, software testing approaches should incorporate slicing methods to make testing more effective and easier. |
| URI: | http://dyuthi.cusat.ac.in/purl/5212 |
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| Dyuthi T-2247.pdf | (3.484Mb) |
| Abstract: | Composite materials have emerged as a superior structural material having application in all spheres of life. These have applications in every sector and essentially in marine environment, where high strength to weight ratio and noncorrosive nature of the material has great importance. Subsequently there has been a major shift in use of structural materials from steel to composite materials in marine structures. Composite materials are engineered materials made from two or more constituent materials that are combined at a macroscopic level to produce a material with characteristics different from the individual components. When both the matrix and fibre are not of metallic origin, such composites are called as nonmetallic composites. Glass Fibre Reinforced Polymers (GFRP), Carbon Fibre Reinforced Polymers (CFRP) and Aramid Fibre Reinforced Polymers (AFRP) are common nonmetallic composite materials used for marine structural applications. These are used in laminate form in ship hull construction.In the present study, a design philosophy based on strength and sustainability of composite laminates has been proposed for selection of composites for ship hull construction. For this purpose, an index based on strength of composite laminates and an index based on sustainability of composites has been tabulated and materials need to be selected based on these indices. Both the indices had been constructed as a composite indicator. Index based on strength called as ‘Strength Index’ has been developed based on the index values of various strength parameters. Index based on sustainability called as ‘Sustainability index’ has been developed based on the index values of the composites based on the environmental impact of various phases of a ship’s life cycle. Nine non metallic composites have been considered in the present study. Accordingly strength parameters identified are bending strength, buckling strength and impact strength have been found out. Environmental impact during the manufacturing phase and disposal phase of composites has been found out. Based on these index values, indices based on strength and sustainability has been constructed respectively. Based on these indices, ranks have been assigned in such a way that, lower rank corresponds to higher strength and lower environmental impact. This also means lower the rank, higher the acceptability of the composite laminates. Using these two indices a two dimensional assessment of composites has been conducted. In this study both the indices have been superimposed to get strength index versus sustainability index plot. Analysis of this plot is the core of the design philosophy, ‘Design for strength and sustainability’. According to this design philosophy, the composite which has the least strength index and sustainability index rank should be selected for designing so that the structure will be strong and at the same time have a low impact on the environment. This procedure can be extended to any number of composites in the marine area or to composites that has application in other areas. |
| URI: | http://dyuthi.cusat.ac.in/purl/5160 |
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| Dyuthi-T2194.pdf | (1.172Mb) |
| Abstract: | Breast cancer detection is an important social requisite as it is the leading cause of death due to cancer among women. The mortality rate of breast cancer is second among all cancers. The cause for breast cancer is not known to date and early detection & treatment are the only means to reduce breast cancer related deaths. Mammography is the main radiological tool that is employed for identifying breast cancer at the earliest stage. Computer aided techniques have great relevance in detection of abnormalities from mammographic images, as often the features associated with various abnormalities are difficult to detect and might be missed by even trained radiologists. In addition, when screening mammography is employed, a large number of mammographic images need to be checked for signs of abnormality, justifying the use of computer aided diagnosis. Three problems are addressed in this thesis: delineation of the pectoral muscle region by properly identifying the pectoral muscle boundary, detection of architectural distortion and enhancement of microcalcification features in the mammographic images. Two novel methods were developed for identifying the pectoral muscle boundary from mediolateral oblique view mammograms that employed multiscale decomposition and local segmentation. The breast area is extracted after this step following the removal of the Pectoral muscle region. The breast abnormalities are searched for in this region. Architectural distortion is the most commonly missed abnormality in mammograms. A novel method for detecting architectural distortion is proposed in this thesis that employs geometrical features obtained from selected edge structures in the mammographic image. These features are used to train a feedforward neural network classifier initialized using metaheuristic algorithms for better classification. Microcalcification is another breast cancer symptom which is ii said to be the most commonly occurring. However the visibility of the microcalcification structures is often poor, especially when they are located in dense parenchymal tissues. Therefore an algorithm is proposed to enhance such features, employing the singularities, viz. zero-crossings and modulus maxima of coefficients obtained after computing the contourlet transform of the mammographic image. Contourlet transform is employed for the directional information it provides. |
| URI: | http://dyuthi.cusat.ac.in/purl/5149 |
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| Dyuthi-T2183.pdf | (10.07Mb) |
| 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) |
| URI: | http://dyuthi.cusat.ac.in/purl/5206 |
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| Dyuthi T-2241.pdf | (11.07Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5187 |
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| Dyuthi T-2222.pdf | (6.684Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5190 |
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| Dyuthi T-2225.pdf | (22.25Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5236 |
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| Dyuthi T-2271.pdf | (15.60Mb) |
| URI: | http://dyuthi.cusat.ac.in/purl/5213 |
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| Dyuthi T-2248.pdf | (3.489Mb) |
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