Rubber Solution Adhesives for Wood-to-Wood Bonding

Rubber solutions were prepared and used for bonding wood pieces. The effect of the variation of chlorinated natural rubber (CNR) and phenolformaldehyde (PF) resin in the adhesive solutions on lap shear strength was determined. Natural rubber and neoprene-based adhesive solutions were compared for their lap shear strength. The storage stability of the adhesive prepared was determined. The change in lap shear strength before and after being placed in cold water, hot water, acid, and alkali was tested. The bonding character of these adhesives was compared with different commercially available solution adhesives. The room-temperature aging resistance of wood joints was also determined. In all the studies, the adhesive prepared in the laboratory was found to be superior compared to the commercial adhesives.

Preparation of high surface area TiO (anatase) by thermal hydrolysis 2 of titanyl sulphate solution

Highly crystalline, ultra fine TiO (anatase) having high surface area has been prepared by thermal hydrolysis of titanyl sulphate 2 solution and characterized using B.E.T surface area measurements, XRD and chemical analysis. The dependence of surface area on concentration of staffing solution, temperature of hydrolysis, duration of boiling and calcination temperature were also studied. As the boiling temperature, duration of boiling and calcination temperature increased, the surface area of TiO formed decreased significantly. 2 On increasing calcination temperature, the crystallite size of TiO also increased and gradually the phase transformation to rutile took 2 place. The onset and completion temperatures of rutilation were 700 and 10008C, respectively

Anomalous variation of thermal lens signal with concentration from rhodamine B in methanol solution

Thermal lens signals in solutions of rhodamine B laser dye in methanol are measured using the dual beam pump-probe technique. The nature of variations of signal strength with concentration is found to be different for 514 and 488 nm Ar + laser excitations. However, both the pump wavelengths produce an oscillatory type variation of thermal lens signal amplitude with the concentration of the dye solution. Probable reasons for this peculiar behaviour (which is absent in the case of fluorescent intensity) are mentioned.

Measurement of the absolute fluorescence quantum yield of rhodamine B solution using a dual-beam thermal lens technique

The dual-beam thermal lens technique has been found to be very effective for the measurement of fluorescence quantum yields of dye solutions. The concentration-dependence of the quantum yield of rhodamine B in methanol is studied here using this technique. The observed results are in line with the conclusion that the reduction in the quantum yield in the quenching region is essentially due to the non-radiative relaxation of the absorbed energy. The thermal lens has been found to become abberated above 40 mW of pump laser power. This low value for the upper limit of pump power is due to the fact that the medium is a resonantly absorbing one.

Photoacoustic signal saturation and optical limiting in C70-toluene solution

Pulsed photoacoustic studies in solutions of C70 in toluene are made using the 532-nm radiation from a frequency-doubled Nd:YAG laser. It is found that contrary to expectation, there is no photoacoustic (PA) signal enhancement in the power-limiting range of laser fluences. Instead, the PA signal tends to saturate during optical power-limiting phenomenon. This could be due to the enhanced optical absorption from the photoexcited state and hence the depletion of the ground-state population. PA measurements also ruled out the possibility of multiphoton absorption in the C70 solution. We demonstrate that the nonlinear absorption leading to optical limiting is mainly due to reverse saturable absorption.

A Study of Photoacoustic Effects and Optical Limiting in the Solution of C60 in Toluene

Pulsed photoacoustic studies in solution of C60 in toluene have been made using the 532 nm radiation from a frequency doubled Nd:YAG laser. Though C60 is found to exhibit the phenomenon of optical limiting, the results on photoacoustic measurements do not give any indication of multiphoton transitions as suggested in some of the earlier works. Results of photoacoustic measurements show that excited state absorption is the dominant process responsible for optical limiting while phenomena like nonlinear scattering may contribute to a lesser extent.

Study of solvent effect in laser emission from Coumarin 540 dye solution

The results of a brief investigation of the amplified spontaneous emission and lasing characteristics of Coumarin 540 dye in as many as ten different solvents are reported. It has been found that C 540 dye solutions contained within a rectangular quartz cuvette give laser emission with well resolved equally spaced modes when pumped with a 476 nm beam. The modes were found to originate from the subcavities formed by the plane-parallel walls of the cuvette containing the high-gain medium. While the quantum yield remains a decisive factor, a clear correlation between the total width of the emission spectra and the refractive indices of the solvents of the respective samples has been demonstrated. The well-resolved mode structure exhibited by the emission spectra gives clear evidence of the lasing action taking place in the gain medium, and the number of modes enables us to compare the gain of the media in different samples. A detailed discussion of the solvent effect in the lasing characteristics of C540 in different solutions is given.

Supramolecular Organization of Metal Nanoparticles in Solution and of Phenyleneethynylenes on Surfaces

Most of the procedures reported for the synthesis of metal nanoparticles involve the use of strong reducing agents or elevated temperatures. This limits the possibility of developing metal nanoparticle based sensors for the in situ detection of analytes. One of the objectives of the present investigations is to (i) develop newer methodologies for the synthesis of metal nanoparticles in aqueous medium at ambient conditions and (ii) their use in the detection of metal cations by taking advantage of the unique coordination ability. Ideally, biocompatible molecules which possess both the reducing and stabilizing groups are desirable for such applications. Formation of stable supramolecular assembly, by bringing metal nanoparticles close to each other, results in plasmon coupling and this strategy can be effectively utilized for the development of metal nanoparticle based sensors.Another objective of the present study is to understand the supramolecular organization of molecules on surfaces. Various noncovalent interactions between the molecules and with surface play a decisive role in their organizations. An in-depth understanding of these interactions is essential for device fabrications. Recent photophysical studies have revealed that phenyleneethynylene based molecular systems are ideal for device application. The second objective of the thesis focuses on understanding the (i) organization of phenyleneethynylenes on highly oriented pyrolytic graphite (HOPG) surface with atomic level precision and (ii) weak intermolecular interactions which drive their organization.

Environmental impact of sand mining

This thesis Entitled Environmental impact of Sand Mining :A case Study in the river catchments of vembanad lake southwest india.The entire study is addressed in nine chapters. Chapter l deals with the general introduction about rivers, problems of river sand mining, objectives, location of the study area and scope of the study. A detailed review on river classification, classic concepts in riverine studies, geological work of rivers and channel processes, importance of river ecosystems and its need for management are dealt in Chapter 2. Chapter 3 gives a comprehensive account of the study area - its location, administrative divisions, physiography, soil, geology, land use and living and non-living resources. The various methods adopted in the study are dealt in Chapter 4. Chapter 5 contains river characteristics like drainage, environmental and geologic setting, channel characteristics, river discharge and water quality of the study area. Chapter 6 gives an account of river sand mining (instream and floodplain mining) from the study area. The various environmental problems of river sand mining on the land adjoining the river banks, river channel, water, biotic and social / human environments of the area and data interpretation are presented in Chapter 7. Chapter 8 deals with the Environmental Impact Assessment (EIA) and Environmental Management Plan (EMP) of sand mining from the river catchments of Vembanad lake.

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.

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

A Data Mining Approach for the Identification of Adverse Drug Events (ADE) resulting from Drug-Drug Interactions (DDI) to improve pharmacovigilance

In the current study, epidemiology study is done by means of literature survey in groups identified to be at higher potential for DDIs as well as in other cases to explore patterns of DDIs and the factors affecting them. The structure of the FDA Adverse Event Reporting System (FAERS) database is studied and analyzed in detail to identify issues and challenges in data mining the drug-drug interactions. The necessary pre-processing algorithms are developed based on the analysis and the Apriori algorithm is modified to suit the process. Finally, the modules are integrated into a tool to identify DDIs. The results are compared using standard drug interaction database for validation. 31% of the associations obtained were identified to be new and the match with existing interactions was 69%. This match clearly indicates the validity of the methodology and its applicability to similar databases. Formulation of the results using the generic names expanded the relevance of the results to a global scale. The global applicability helps the health care professionals worldwide to observe caution during various stages of drug administration thus considerably enhancing pharmacovigilance

Reinforcement Learning Solution for Unit Commitment Problem Considering Minimum Start Up and Shut Down Times

Unit Commitment Problem (UCP) in power system refers to the problem of determining the on/ off status of generating units that minimize the operating cost during a given time horizon. Since various system and generation constraints are to be satisfied while finding the optimum schedule, UCP turns to be a constrained optimization problem in power system scheduling. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision making task and an efficient Reinforcement Learning solution is formulated considering minimum up time /down time constraints. The correctness and efficiency of the developed solutions are verified for standard test systems

Reinforcement Learning solution for Unit Commitment Problem through pursuit method

Unit commitment is an optimization task in electric power generation control sector. It involves scheduling the ON/OFF status of the generating units to meet the load demand with minimum generation cost satisfying the different constraints existing in the system. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision task and Reinforcement Learning solution is formulated through one efficient exploration strategy: Pursuit method. The correctness and efficiency of the developed solutions are verified for standard test systems