Microbent optical fibers as evanescent wave sensors

Microbent optical fibers are potential candidates for evanescent wave sensing. We investigate the behavior of a permanently microbent fiber optic sensor when it is immersed in an absorbing medium. Two distinct detection schemes, namely, bright-field and dark-field detection configuration, are employed for the measurements. The optical power propagating through the sensor is found to vary in a logarithmic fashion with the concentration of the absorbing species in the surrounding medium. We observe that the sensitivity of the setup is dependent on the bending amplitude and length of the microbend region for the bright-field detection scheme, while it is relatively independent of both for the dark-field detection configuration. This feature can be exploited in compact sensor designs where reduction of the sensing region length is possible without sacrificing sensitivity.

Magnetic field-induced cluster formation and variation of magneto-optical signals in zinc-substituted ferrofluids

Fine magnetic particles (size≅100 Å) belonging to the series ZnxFe1−xFe2O4 were synthesized by cold co-precipitation methods and their structural properties were evaluated using X-ray diffraction. Magnetization studies have been carried out using vibrating sample magnetometry (VSM) showing near-zero loss loop characteristics. Ferrofluids were then prepared employing these fine magnetic powders using oleic acid as surfactant and kerosene as carrier liquid by modifying the usually reported synthesis technique in order to induce anisotropy and enhance the magneto-optical signals. Liquid thin films of these fluids were prepared and field-induced laser transmission through these films was studied. The transmitted light intensity decreases at the centre with applied magnetic field in a linear fashion when subjected to low magnetic fields and saturate at higher fields. This is in accordance with the saturation in cluster formation. The pattern exhibited by these films in the presence of different magnetic fields was observed with the help of a CCD camera and was recorded photographically.

Design and Development of data mining models for the predictions of manpower placement in the technical Domain

Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.

Studies on the universal parameters and onset of chaos in dissipative systems

It has become clear over the last few years that many deterministic dynamical systems described by simple but nonlinear equations with only a few variables can behave in an irregular or random fashion. This phenomenon, commonly called deterministic chaos, is essentially due to the fact that we cannot deal with infinitely precise numbers. In these systems trajectories emerging from nearby initial conditions diverge exponentially as time evolves)and therefore)any small error in the initial measurement spreads with time considerably, leading to unpredictable and chaotic behaviour The thesis work is mainly centered on the asymptotic behaviour of nonlinear and nonintegrable dissipative dynamical systems. It is found that completely deterministic nonlinear differential equations describing such systems can exhibit random or chaotic behaviour. Theoretical studies on this chaotic behaviour can enhance our understanding of various phenomena such as turbulence, nonlinear electronic circuits, erratic behaviour of heart and brain, fundamental molecular reactions involving DNA, meteorological phenomena, fluctuations in the cost of materials and so on. Chaos is studied mainly under two different approaches - the nature of the onset of chaos and the statistical description of the chaotic state.

“Synthesis and Photochemical Transformations of a few Tethered Barrelenes”

the author has designed few barrelene molecules in such a way that the structural features of these compounds will enable them to undergo intriguing triplet state mediated di- -methane rearrangement. The strategy involved the preparation of dibenzobarrelenes appended with a fused ring systems, thereby restricting the rotational freedom of the bridgehead substituent. We describe these systems as ‘tethered barrelenes’. These tethered barrelenes enabled us to examine the effect of orientation and the nature of the bridgehead-substituents in controlling the regioselectivity of di-π-methane rearrangement in a more systematic fashion. In this background, the thesis entitled “SYNTHESIS AND PHOTOCHEMICAL TRANSFORMATIONS OF A FEW TETHERED BARRELENES” reveals our attempts to explore the factors controlling the regioselectivity of di-π-methane rearrangement displayed by dibenzobarrelenes. Moreover, we have observed interesting dark reactions of suitable substituted tethered dibenzosemibullvalenes in a few cases

“Reconstruction of Gene Regulatory Network from Expression Profile of Plasma RNA Data of Colorectal Cancer Patients using Soft Computing Techniques”

Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

“Studies on new base materials for microcellular soles"

The most important part of any footwear is the sole (or sole and heel) which withstands all the hannful external factors such as rouglmess of the ground or road, sharp objects, thorns and stones, heat, dampness and cold during walking. The properties desirable in soling material, therefore, would be 1. lightness 2. resistance to wear and tear for long service life 3. flexibility/softness for wearing comfort 4. thennal insulation Rubber soling surpasses all other soling materials in better performance and lower cost. Because MC sole is soft and very light, and has good abrasion resistance, flex properties and set behaviour it has become very popular all over the world and demand for better quality product is ever increasing. Due to the traditional approach adopted by the footwear industry in foot wear design, the rubber based footwear export surprisingly contributes only a small percentage. The essence of success for any industry lies in the expansion of the export market. Microcellular soles are manufactured for the last three decades without much change in the traditional design and colour pattern. In recent years domestic customers have also started demanding better quality products. In view of the changing taste of the customer and growing competition from other countries, substantial improvement in the export potential will require new base materials for regular or fashion rubber based footwears. The main objective of the present study is to develop new base materials for making MC soles with good quality, viz., light weight, durability and bright colours

Magnetic field-induced cluster formation and variation of magneto-optical signals in zinc-substituted ferrofluids

Fine magnetic particles (sizeffi100A ˚ ) belonging to the series ZnxFe1 xFe2O4 were synthesized by cold co-precipitation methods and their structural properties were evaluated using X-ray diffraction. Magnetization studies have been carried out using vibrating sample magnetometry (VSM) showing near-zero loss loop characteristics. Ferrofluids were then prepared employing these fine magnetic powders using oleic acid as surfactant and kerosene as carrier liquid by modifying the usually reported synthesis technique in order to induce anisotropy and enhance the magneto-optical signals. Liquid thin films of these fluids were prepared and field-induced laser transmission through these films was studied. The transmitted light intensity decreases at the centre with applied magnetic field in a linear fashion when subjected to low magnetic fields and saturate at higher fields. This is in accordance with the saturation in cluster formation. The pattern exhibited by these films in the presence of different magnetic fields was observed with the help of a CCD camera and was recorded photographically