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This study explores the utilization of Binary Embedded Zero Tree Wavelet Algorithms (BEZW) to compress hyperspectral images. The primary goal is to enhance the representation of spectral data while minimizing storage and transmission requirements. The BEZW algorithm employs wavelet transformations to leverage both spectral and spatial redundancies found in hyperspectral data cubes. Its embedded zero tree structure ensures efficient encoding of small coefficients with minimal overhead. The study evaluates the performance of the BEZW method utilizing various hyper-spectral datasets and compression settings, comparing it to other compression techniques. The results illustrate that the BEZW algorithm offers a promising approach to hyperspectral image compression, achieving competitive compression ratios while preserving spectral accuracy. This makes it a valuable option for applications where efficient hyperspectral data storage and transmission are crucial. The research contributes to the field of hyperspectral imaging by introducing an effective compression method that enhances data accessibility, simplifying the utilization of hyperspectral data in resource-constrained environments. [ABSTRACT FROM AUTHOR]

The EU co-funded project Advanced Research Infrastructure for Archaeological Dataset Networking in Europe (ARIADNE) aims to integrate data and services across Europe for the archaeological research community. The Discovery Programme has investigated data holdings and management practices in Irish archaeology, focusing on what information is available in physical and digital forms, approaches to preservation and accessibility, and the challenges and opportunities around dataset networking with Irish archaeological data. While significant work will be required to enable the accessibility expected by researchers now and in future, there is also an opportunity to approach the challenges of digital preservation as a community. [ABSTRACT FROM AUTHOR]

Background: Research training for public health professionals is key to the future of public health and policy in Africa. A growing number of schools of public health are connected to health and socio-demographic surveillance system field sites in developing countries, in Africa and Asia in particular. Linking training programs with these sites provides important opportunities to improve training, build local research capacity, foreground local health priorities, and increase the relevance of research to local health policy. Objective: To increase research training capacity in public health programs by providing targeted training to students and increasing the accessibility of existing data. Design: This report is a case study of an approach to linking public health research and training at the University of the Witwatersrand. We discuss the development of a sample training database from the Agincourt Health and Socio-demographic Surveillance System in South Africa and outline a concordant transnational intensive short course on longitudinal data analysis offered by the University of the Witwatersrand and the University of Colorado-Boulder. This case study highlights ways common barriers to linking research and training can be overcome. Results and Conclusions: This collaborative effort demonstrates that linking training to ongoing data collection can improve student research, accelerate student training, and connect students to an international network of scholars. Importantly, the approach can be adapted to other partnerships between schools of public health and longitudinal research sites. [ABSTRACT FROM AUTHOR]