E-marketing motivators,inhibitors and critical success factors: A study of small and medium tourism enterprises (SMTES) in Mauritius and Andaman islands, India

Information and Communication Technologies (ICTs) have a dramatic impact on the tourism industry because they force this sector as a whole to rethink the way in which it organises its business . In the light of such rethinking within the tourism industry, this study has focussed on the Small and Medium Tourism Enterprises (SMTEs) in two island destinations, namely Mauritius and Andaman Islands, India.Suggestions. The findings conceming SMTEs in Mauritius and Andaman Islands have been compared to make some destination-specific inferences. The relevance of the findings has been discussed with reference to the SMTEs in the two destinations as well as the possible acceptability in other comparable settings. Suggestions have been made for further research in SMTEs’ use of the Internet for marketing function.

Free/Open Source Software in CUSAT: A Success Story

Free/Open Source Software (FOSS) concept is very important in the academic community. The open philosophy of FOSS is consistent with academic freedom and the open dissemination of knowledge and information in academia. FOSS can lower the barriers to access of ICTs by reducing the cost of the software. This article discusses the success story of CUSAT's adoption of Free/Open Source Software

Image Denoising Using Sure-Based Adaptive Thresholding In Directionlet Domain

The standard separable two dimensional wavelet transform has achieved a great success in image denoising applications due to its sparse representation of images. However it fails to capture efficiently the anisotropic geometric structures like edges and contours in images as they intersect too many wavelet basis functions and lead to a non-sparse representation. In this paper a novel de-noising scheme based on multi directional and anisotropic wavelet transform called directionlet is presented. The image denoising in wavelet domain has been extended to the directionlet domain to make the image features to concentrate on fewer coefficients so that more effective thresholding is possible. The image is first segmented and the dominant direction of each segment is identified to make a directional map. Then according to the directional map, the directionlet transform is taken along the dominant direction of the selected segment. The decomposed images with directional energy are used for scale dependent subband adaptive optimal threshold computation based on SURE risk. This threshold is then applied to the sub-bands except the LLL subband. The threshold corrected sub-bands with the unprocessed first sub-band (LLL) are given as input to the inverse directionlet algorithm for getting the de-noised image. Experimental results show that the proposed method outperforms the standard wavelet-based denoising methods in terms of numeric and visual quality