Dielectric Studies of Corn Syrup for Applications in Microwave Breast Imaging

Permittivity and conductivity studies of corn syrup in various concentrations are performed using coaxial cavity perturbation technique over a frequency range of 250 MHz–3000 MHz. The results are utilized to estimate relaxation time and dipole moments of the samples. The stability of the material over the variations of time is studied. The measured specific absorption rate of the material complies with the microwave power absorption rate of biological tissues. This suggests the feasibility of using corn syrup as a suitable, cost effective coupling medium for microwave breast imaging. The material can also be used as an efficient breast phantom in microwave breast imaging studies.

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.

Development and Investigations of Mobile Antennas for less Radiation Hazards

Antennas, the key element in wireless communication devices had undergone amazing developments especially in the direction of compactness and safety aspects. In the last two decades, the use of the cellular phones has become the most popular mode of communication across the globe. At the same time, the concerns about the radiation effects have increased in the general public. The main concern of this thesis is to develop a mobile antenna which gives reduced RF interference to the user. The reduction of the power absorbed by the user can tremendously avoid any possible health hazards. The radiation characteristic of a monopole antenna is modified with good radiation characteristics suitable for a mobile handset. The modification is implemented by using different resonating structures which provides reduced radiation along one direction. The direction of less radiation can be changed by modifying the planar antenna structure to a ground folded antenna. This modified structure with excellent radiation characteristic is suitable for modern wireless handheld devices with less user RF interference. Specific Absorption Rate (SAR) is an important parameter for mobile handset. The SAR is estimated for the newly developed antenna for different conditions and discussed in this thesis.

Applying Data mining using Statistical Techniques for Career Selection

For years, choosing the right career by monitoring the trends and scope for different career paths have been a requirement for all youngsters all over the world. In this paper we provide a scientific, data mining based method for job absorption rate prediction and predicting the waiting time needed for 100% placement, for different engineering courses in India. This will help the students in India in a great deal in deciding the right discipline for them for a bright future. Information about passed out students are obtained from the NTMIS ( National technical manpower information system ) NODAL center in Kochi, India residing in Cochin University of science and technology