Selection and Floral Evolution in Platanthera bifolia and P. chlorantha (Orchidaceae)

Natural selection mediated by pollinators has influenced the evolution of floral diversity of the flowering plants (angiosperms). The scope of this thesis was to study: 1) phenotypic selection, 2) mating systems, and 3) floral shifts involved in plant speciation. Model plant species were Platanthera bifolia and P. chlorantha (Orchidaceae). These orchids are moth-pollinated, strictly co-sexual (bisexual flowers), and produce a spike that displays 10-20 white flowers. I explored the influence of characters on plant fitness by using multiple linear regressions. Pollen removal (male fitness) and fruit set (female fitness) increased with more flowers per plant in three P. bifolia populations. There was selection towards longer spurs in a dry year when average spur length was shorter than in normal-wet years. Female function was sensitive to drought, which enabled an application of the male function hypothesis of floral evolution (Bateman's principle). The results show that selection may vary between populations, years, and sex-functions. I examined inbreeding by estimating levels of geitonogamy (self-pollination between flowers of an individual) with an emasculation method in two P. bifolia populations. Geitonogamy did not vary with inflorescence size. Levels of geitonogamy was 20-40% in the smaller, but non-significant in the larger population. This may relate to lower number of possible mates and pollinator activity in the smaller population. Platanthera bifolia exhibits the ancestral character state of tongue-attachment of pollinia on the pollinator. Its close relative P. chlorantha attaches its pollinia onto the pollinator's eyes. To explore the mechanism of a floral shift, pollination efficiency and speed was compared between the two species. The results showed no differences in pollination efficiency, but P. chlorantha had faster pollen export and import. Efficiency of pollination in terms of speed may cause floral shifts, and thus speciation.

Soft computing in biometrics : a pragmatic appraisal

The ever increasing spurt in digital crimes such as image manipulation, image tampering, signature forgery, image forgery, illegal transaction, etc. have hard pressed the demand to combat these forms of criminal activities. In this direction, biometrics - the computer-based validation of a persons' identity is becoming more and more essential particularly for high security systems. The essence of biometrics is the measurement of person’s physiological or behavioral characteristics, it enables authentication of a person’s identity. Biometric-based authentication is also becoming increasingly important in computer-based applications because the amount of sensitive data stored in such systems is growing. The new demands of biometric systems are robustness, high recognition rates, capability to handle imprecision, uncertainties of non-statistical kind and magnanimous flexibility. It is exactly here that, the role of soft computing techniques comes to play. The main aim of this write-up is to present a pragmatic view on applications of soft computing techniques in biometrics and to analyze its impact. It is found that soft computing has already made inroads in terms of individual methods or in combination. Applications of varieties of neural networks top the list followed by fuzzy logic and evolutionary algorithms. In a nutshell, the soft computing paradigms are used for biometric tasks such as feature extraction, dimensionality reduction, pattern identification, pattern mapping and the like.