2 resultados para Computational Intelligence in data-driven and hybrid Models and Data Analysis
em Digital Commons @ DU | University of Denver Research
Resumo:
Understanding spatial distributions and how environmental conditions influence catch-per-unit-effort (CPUE) is important for increased fishing efficiency and sustainable fisheries management. This study investigated the relationship between CPUE, spatial factors, temperature, and depth using generalized additive models. Combinations of factors, and not one single factor, were frequently included in the best model. Parameters which best described CPUE varied by geographic region. The amount of variance, or deviance, explained by the best models ranged from a low of 29% (halibut, Charlotte region) to a high of 94% (sablefish, Charlotte region). Depth, latitude, and longitude influenced most species in several regions. On the broad geographic scale, depth was associated with CPUE for every species, except dogfish. Latitude and longitude influenced most species, except halibut (Areas 4 A/D), sablefish, and cod. Temperature was important for describing distributions of halibut in Alaska, arrowtooth flounder in British Columbia, dogfish, Alaska skate, and Aleutian skate. The species-habitat relationships revealed in this study can be used to create improved fishing and management strategies.
Resumo:
The purpose of this study is multifaceted: 1) to describe eScience research in acomprehensive way; 2) to help library and information specialists understand the realm of eScience research and the information needs of the community and demonstrate the importance of LIS professionals within the eScience domain; 3) and to explore the current state of curricular content of ALA accredited MLS/MLIS programs to understand the extent to which they prepare new professionals within eScience librarianship. The literature review focuses heavily on eScientists and other data-driven researchers’ information service needs in addition to demonstrating how and why librarians and information specialists can and should fulfill these service gaps and information needs within eScience research. By looking at the current curriculum of American Library Association (ALA) accredited MLS/MLIS programs, we can identify potential gaps in knowledge and where to improve in order to prepare and train new MLS/MLIS graduates to fulfill the needs of eScientists. This investigation is meant to be informative and can be used as a tool for LIS programs to assess their curriculums in comparison to the needs of eScience and other data-driven and networked research. Finally, this investigation will provide awareness and insight into the services needed to support a thriving eScience and data-driven research community to the LIS profession.