The electrical conductivity and thermoelectric power of some lithium–titanium ferrites with small amounts of manganese and zinc have been studied as a function of temperature in the range of 300–550 K and are reported here. The conductivity variation shows two different regions with a large variation in the activation energies. The possible mechanisms with respect to ionic conduction and electron hopping are discussed with the support of thermoelectric power measurements. Lattice parameters are also calculated from x-ray diffractograms for confirming the single-phase nature of the ferrites.

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Slender cylindrical members form the major components of many of the coastal and offshore structures. These members are frequently subjected to breaking wave impact which often resulted in damages and failure of structures. In order to overcome this intricacy, it is essential to understand the physics of the breaking wave impact on offshore structural members and the resulting induced critical stresses. An experimental investigation has been carried out to measure the effect of breaking wave impact on a slender vertical cylinder. Simultaneous qualitative visual observations and quantitative pressure measurements were made to appreciate the impact induced effect. The induced impact pressure on the cylinder varies with the intensity of wave breaking and the relative location of the cylinder. The impact pressure is maximum when the wave profile reaches its maximum steepness just before the crest destabilization. Impact pressure observed due to a severe plunging wave is about nine times higher than due to spilling. The pressure rise time is found to be an important parameter in dictating the nature of impact.

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Mining the content from an information database provides challenging solutions to the industry experts and researchers, due to the overcrowded information in huge data. In web searching, the information retrieved is not an appropriate, because it gives ambiguous information for the user query, and the user cannot get relevant information within the stipulated time. To overcome these issues, we propose a new methodology for information retrieval EPCRR by providing the top most exact information to the user, by using the collaborative clustered automated filter which makes use of the collaborative data set and filter works on the prediction by providing the highest ranking for the exact data retrieved. The retrieval works on the basis of recommendation of data which consists of relevant data set with highest priority from the cluster of data which is on high usage. In this work, we make use of the automated wrapper which works similar to the meta crawler functionality and it obtains the content in the semantic usage data format. Obtained information from the user to the agent will be ranked based on the Enabled Pile clustered data with respect to the metadata information from the agent and end-user. The information is given to the end-user with the top most ranking data within the stipulated time and the remaining top information will be moved to the data repository for future use. The data collected will remain stable based on the user preference and works on the intelligence system approach in which the user can choose any information under any instances and can be provided with suitable high range of exact content. In this approach, we find that the proposed algorithm has produced better results than existing work and it costs less online computation time.