The hidden costs of cheap group tours - a case study of business practices in Australia

This paper deals with an issue that has been identified in many markets where there are large numbers of package tourists. In Australia, there have been a number of studies undertaken into the use of a range of dubious business practices employed by Inbound Tour Operators (ITOs), particularly in the Korean market. The cause for this problem is identified as the minimization of the retail price of package tour by transferring part of the cost of the tour to ITOs in the destination country. Under this system, ITOs are paid a daily tour rate below their real costs and are forced to recover losses by employing a range of dubious business practices including forced shopping and kickbacks from shops. The paper models the normal operation of the package tour cycle where no business practices are used and compares this to the Korean package inbound market in Australia where the use of business practices of this nature is widespread

Genetic homogeneity and phage susceptibility of ruminal strains of Streptococcus bovis isolated in Australia

The genetic homogeneity of 37 strains of ruminal streptococci was investigated by comparing DNA fragment profiles on agarose gels following restriction endonuclease digestion with Hae III, Cfo I and Msp I. Thirty strains were indistinguishable from Streptococcus bovis strains, 2B, H24 and AR3. The remaining three strains were similar but not identical to a ruminal strain of Strep. intermedius (AR36). In addition, the susceptibility of these strains to infection by five bacteriophages was examined. Three of the phages (φSb02, φSb03 and φSb04) were specific to the strain of Strep. bovis from which they were isolated, while phages 2BV and φSb01 infected one and two strains, respectively, in addition to their primary host. It was concluded that although Strep. bovis is relatively homogeneous genetically, broad host range phages appear to be uncommon with this bacterial species

Analysis of electrochemical noise data by use of recurrence quantification analysis and machine learning methods

© 2017 By use of recurrence quantification analysis (RQA), twelve features were extracted from the electrochemical noise signals generated by three types of corrosion: uniform, pitting and passivation. Machine learning methods, i.e. linear discriminant analysis (LDA) and random forests (RF), were used to identify the different corrosion types from those features. Both models gave satisfactory performance, but the RF model showed better prediction accuracy of 93% than the LDA model (88%). Furthermore, an estimation of the importance of the variables by use of the RF model suggested the RQA variables laminarity (LAM) and determinism (DET) played the most significant role with regard to identification of corrosion types. In addition, the comparison of noise resistance with the resistance obtained from EIS measurement showed that the noise resistance can be used for monitoring corrosion rate variations not only for uniform corrosion and passivation, but also for pitting