A decade of monitoring Atlantic cod Gadus morhua spawning aggregations in Massachusetts Bay using passive acoustics

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Caiger, P. E., Dean, M. J., DeAngelis, A. I., Hatch, L. T., Rice, A. N., Stanley, J. A., Tholke, C., Zemeckis, D. R., & Van Parijs, S. M. A decade of monitoring Atlantic cod Gadus morhua spawning aggregations in Massachusetts Bay using passive acoustics. Marine Ecology Progress Series, 635, (2020): 89-103, doi:10.3354/meps13219.Atlantic cod Gadus morhua populations in the northeast USA have failed to recover since major declines in the 1970s and 1990s. To rebuild these stocks, managers need reliable information on spawning dynamics in order to design and implement control measures; discovering cost-effective and non-invasive monitoring techniques is also favorable. Atlantic cod form dense, site-fidelic spawning aggregations during which they vocalize, permitting acoustic detection of their presence at such times. The objective of this study was to detect spawning activity of Atlantic cod using multiple fixed-station passive acoustic recorders to sample across Massachusetts Bay during the winter spawning period. A generalized linear modeling approach was used to investigate spatio-temporal trends of cod vocalizing over 10 consecutive winter spawning seasons (2007-2016), the longest such timeline of any passive acoustic monitoring of a fish species. The vocal activity of Atlantic cod was associated with diel, lunar, and seasonal cycles, with a higher probability of occurrence at night, during the full moon, and near the end of November. Following 2009 and 2010, there was a general decline in acoustic activity. Furthermore, the northwest corner of Stellwagen Bank was identified as an important spawning location. This project demonstrated the utility of passive acoustic monitoring in determining the presence of an acoustically active fish species, and provides valuable data for informing the management of this commercially, culturally, and ecologically important species.Thanks to Eli Bonnell, Genevieve Davis, Julianne Bonell, Samara Haver, and Eric Matzen for assistance in MARU deployments, Dana Gerlach and Heather Heenehan for help in passive acoustic data analysis, and the NEFSC passive acoustics group for useful discussions. Funding for 2007−2012 passive acoustic surveys was provided by Excelerate Energy and Neptune LNG to Cornell University. Fieldwork for 2013−2015 was funded through the 2013−2014 NOAA Saltonstall-Kennedy grant program (Award No. NA14NMF4270027), and jointly funded by The Nature Conservancy, Massachusetts Division of Marine Fisheries, and the Cabot Family Charitable Foundation. Funding for 2016 SoundTrap data was provided by NOAA’s Ocean Acoustics Program (4 Sanctuaries Project)

Hierarchical structuring of Cultural Heritage objects within large aggregations

Huge amounts of cultural content have been digitised and are available through digital libraries and aggregators like Europeana.eu. However, it is not easy for a user to have an overall picture of what is available nor to find related objects. We propose a method for hier- archically structuring cultural objects at different similarity levels. We describe a fast, scalable clustering algorithm with an automated field selection method for finding semantic clusters. We report a qualitative evaluation on the cluster categories based on records from the UK and a quantitative one on the results from the complete Europeana dataset.Comment: The paper has been published in the proceedings of the TPDL conference, see http://tpdl2013.info. For the final version see http://link.springer.com/chapter/10.1007%2F978-3-642-40501-3_2

Generating natural language specifications from UML class diagrams

Early phases of software development are known to be problematic, difficult to manage and errors occurring during these phases are expensive to correct. Many systems have been developed to aid the transition from informal Natural Language requirements to semistructured or formal specifications. Furthermore, consistency checking is seen by many software engineers as the solution to reduce the number of errors occurring during the software development life cycle and allow early verification and validation of software systems. However, this is confined to the models developed during analysis and design and fails to include the early Natural Language requirements. This excludes proper user involvement and creates a gap between the original requirements and the updated and modified models and implementations of the system. To improve this process, we propose a system that generates Natural Language specifications from UML class diagrams. We first investigate the variation of the input language used in naming the components of a class diagram based on the study of a large number of examples from the literature and then develop rules for removing ambiguities in the subset of Natural Language used within UML. We use WordNet,a linguistic ontology, to disambiguate the lexical structures of the UML string names and generate semantically sound sentences. Our system is developed in Java and is tested on an independent though academic case study

Enabling Micro-level Demand-Side Grid Flexiblity in Resource Constrained Environments

The increased penetration of uncertain and variable renewable energy presents various resource and operational electric grid challenges. Micro-level (household and small commercial) demand-side grid flexibility could be a cost-effective strategy to integrate high penetrations of wind and solar energy, but literature and field deployments exploring the necessary information and communication technologies (ICTs) are scant. This paper presents an exploratory framework for enabling information driven grid flexibility through the Internet of Things (IoT), and a proof-of-concept wireless sensor gateway (FlexBox) to collect the necessary parameters for adequately monitoring and actuating the micro-level demand-side. In the summer of 2015, thirty sensor gateways were deployed in the city of Managua (Nicaragua) to develop a baseline for a near future small-scale demand response pilot implementation. FlexBox field data has begun shedding light on relationships between ambient temperature and load energy consumption, load and building envelope energy efficiency challenges, latency communication network challenges, and opportunities to engage existing demand-side user behavioral patterns. Information driven grid flexibility strategies present great opportunity to develop new technologies, system architectures, and implementation approaches that can easily scale across regions, incomes, and levels of development

Regional environmental analysis and management: New techniques for current problems

Advances in data acquisition and processing procedures for regional environmental analysis are discussed. Automated and semi-automated techniques employing Earth Resources Technology Satellite data and conventional data sources are presented. Experiences are summarized. The ERTS computer compatible tapes provide a very complete and flexible record of earth resources data and represent a viable medium to enhance regional environmental analysis research

From Artifacts to Aggregations: Modeling Scientific Life Cycles on the Semantic Web

In the process of scientific research, many information objects are generated, all of which may remain valuable indefinitely. However, artifacts such as instrument data and associated calibration information may have little value in isolation; their meaning is derived from their relationships to each other. Individual artifacts are best represented as components of a life cycle that is specific to a scientific research domain or project. Current cataloging practices do not describe objects at a sufficient level of granularity nor do they offer the globally persistent identifiers necessary to discover and manage scholarly products with World Wide Web standards. The Open Archives Initiative's Object Reuse and Exchange data model (OAI-ORE) meets these requirements. We demonstrate a conceptual implementation of OAI-ORE to represent the scientific life cycles of embedded networked sensor applications in seismology and environmental sciences. By establishing relationships between publications, data, and contextual research information, we illustrate how to obtain a richer and more realistic view of scientific practices. That view can facilitate new forms of scientific research and learning. Our analysis is framed by studies of scientific practices in a large, multi-disciplinary, multi-university science and engineering research center, the Center for Embedded Networked Sensing (CENS).Comment: 28 pages. To appear in the Journal of the American Society for Information Science and Technology (JASIST