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- Creators: ASU Library. Music Library
This study examines the creation of a sustainability toolkit that can be implemented in many communities, beginning with Johnson City, Tennessee. This project began in 2019 and will continue to grow indefinitely. For this project, a toolkit that will allow the public to have access to the tools and information they need in order to make their homes more energy-efficient will be created. It will be stocked in the local library in Johnson City Tennessee for free use to the public, as long as they have a library card, they can check out the toolkits. The toolkits will be used by the public, then returned to the library so that they can be restocked and checked out again. This study looks at the market, business and organizational research and the infrastructure of the project. Methods of research included looking at how the need for a change came about, who will benefit, existing similar programs and how they will be used in conjunction with this project, current organizational structures attached to the project, current team infrastructure and what resources are needed to fill the voids. Findings include what financial resources will be required and how they will be acquired, as well as resources that are currently available for this project and what is still needed in order for this project to be successful. As a result of this project, at least two libraries in the Johnson City area will be stocked with several energy toolkits for free and a partnership for future project expansion will have been established. This study looks at the process and what was learned during the implementation of the project.
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.