Influence of compounding and process variables on quality of condams made from natural rubber latex

Condoms are widely accepted as a contraceptive for family planning and population control. It is also accepted as the most effective barrier against sexually transmitted diseases, especially AIDS, the incurable disease. But presence of pinholes and low film strength of condoms make it unsuitable for the purpose. Quality improvement of condoms by reducing the pinhole formation and increasing the film strength is thus an essential requirement for population control as well as for preventing the spread of sexually transmitted diseases. Strict implementation of WHO specification of condoms further increases the rejection percentage. This causes higher rejection loss to condom manufacturers because the defects could be identified only at the final stage of processing. If the influence of various factors which cause these defects is known, manufacturers can take remedial measures to reduce the defectives so that rejection loss can be decreased and quality of condoms increased. In the present study, it was proposed to conduct experiments to improve the quality of condoms by reducing the pinhole rejection percentage and increasing the tensile properties, burst volume, and burst pressure. Ageing property improvement also was an important target among other parameters. Until a cure for AIDS is found, a high quality latex condom is the only effective device in the prevention of the spread of HIV, AIDS and STD's. Hence it is all the more necessary to have high quality condoms.

Development of an instrument to assess Human Resource Quality (HRQ) and measuring the impact of TQM efforts on HRQ using the instrument

This research is aimed at developing an instrument for measuring human resource quality in organizations. The researcher has developed the instrument for measuring HRQ based on extensive literature survey and expert opinion. Statistical validity of the Instrument has also been established. This instrument was used to measure the changes in Human Resource Quality in selected organizations wherein quality management practices are being implemented. Data collected was analyzed and presented in this thesis. It has been found that there are significant changes in all the indicators of Human Resource Quality. There is improvement in Cultural Change Index(CCI), Quality of Work Life Index(QWLI) and Employee Satisfaction Index(ESI). The Human Resource Quality index has also increased significantly in all the organizations. It has been observed from the study that implementation of TQM leads to significant changes in Human Resource Quality. This instrument is capable of measuring minor variations in each indicator of HRQ and can be used to identify areas of weakness and strength in the case of Human Resource Quality. The instrument can further be modified by future research. This research work provided excellent opportunities for the researcher for self-development and has made him confident to undertake such activities for the benefit of the learning community.

Performance Improvement of Fuzzy and Neuro Fuzzy Systems: Prediction of Learning Disabilities in School-age Children

Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.