How single is ‘single’ : some pragmatic reflections on single versus multifaceted interventions to facilitate implementation

An earlier overview of systematic reviews and a subsequent editorial on single-component versus multifaceted interventions to promote knowledge translation (KT) highlight complex issues in implementation science. In this supplemented commentary, further aspects are in focus; we propose examples from (KT) studies probing the issue of single interventions. A main point is that defining what is a single and what is a multifaceted intervention can be ambiguous, depending on how the intervention is conceived. Further, we suggest additional perspectives in terms of strategies to facilitate implementation. More specifically, we argue for a need to depict not only what activities are done in implementation interventions, but to unpack functions in particular contexts, in order to support the progress of implementation science.

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.