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      ABS-FishCount: An Agent-Based Simulator of Underwater Sensors for Measuring the Amount of Fish

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          Abstract

          Underwater sensors provide one of the possibilities to explore oceans, seas, rivers, fish farms and dams, which all together cover most of our planet’s area. Simulators can be helpful to test and discover some possible strategies before implementing these in real underwater sensors. This speeds up the development of research theories so that these can be implemented later. In this context, the current work presents an agent-based simulator for defining and testing strategies for measuring the amount of fish by means of underwater sensors. The current approach is illustrated with the definition and assessment of two strategies for measuring fish. One of these two corresponds to a simple control mechanism, while the other is an experimental strategy and includes an implicit coordination mechanism. The experimental strategy showed a statistically significant improvement over the control one in the reduction of errors with a large Cohen’s d effect size of 2.55.

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          Statistical Power Analysis for the Behavioral Sciences

          Jacob Cohen (2013)
          <i>Statistical Power Analysis</i> is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: <br> * a chapter covering power analysis in set correlation and multivariate methods;<br> * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and;<br> * expanded power and sample size tables for multiple regression/correlation.<br>
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            Underwater acoustic sensor networks: research challenges

            Ian F. Akyildiz, Dario Pompili, Tommaso Melodia (2005)
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              Remote bioenergetics measurements in wild fish: Opportunities and challenges.

              Steven Cooke, Jacob Brownscombe, Graham Raby … (2016)
              The generalized energy budget for fish (i.e., Energy Consumed=Metabolism+Waste+Growth) is as relevant today as when it was first proposed decades ago and serves as a foundational concept in fish biology. Yet, generating accurate measurements of components of the bioenergetics equation in wild fish is a major challenge. How often does a fish eat and what does it consume? How much energy is expended on locomotion? How do human-induced stressors influence energy acquisition and expenditure? Generating answers to these questions is important to fisheries management and to our understanding of adaptation and evolutionary processes. The advent of electronic tags (transmitters and data loggers) has provided biologists with improved opportunities to understand bioenergetics in wild fish. Here, we review the growing diversity of electronic tags with a focus on sensor-equipped devices that are commercially available (e.g., heart rate/electrocardiogram, electromyogram, acceleration, image capture). Next, we discuss each component of the bioenergetics model, recognizing that most research to date has focused on quantifying the activity component of metabolism, and identify ways in which the other, less studied components (e.g., consumption, specific dynamic action component of metabolism, somatic growth, reproductive investment, waste) could be estimated remotely. We conclude with a critical but forward-looking appraisal of the opportunities and challenges in using existing and emerging electronic sensor-tags for the study of fish energetics in the wild. Electronic tagging has become a central and widespread tool in fish ecology and fisheries management; the growing and increasingly affordable toolbox of sensor tags will ensure this trend continues, which will lead to major advances in our understanding of fish biology over the coming decades.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sensors (Basel)
                Journal ID (iso-abbrev): Sensors (Basel)
                Journal ID (publisher-id): sensors
                Title: Sensors (Basel, Switzerland)
                Publisher: MDPI
                ISSN (Electronic): 1424-8220
                Publication date (Electronic): 13 November 2017
                Publication date Collection: November 2017
                Volume: 17
                Issue: 11
                Electronic Location Identifier: 2606
                Affiliations
                [1 ]Department of Computer Science and Engineering of Systems, University of Zaragoza, 44003 Teruel, Spain; lacuesta@ 123456unizar.es
                [2 ]Instituto de Investigación Sanitaria Aragón, University of Zaragoza, 50009 Zaragoza, Spain
                [3 ]Integrated Management Coastal Research Institute, Universitat Politècnica de València, 46022 València, Spain; jlloret@ 123456dcom.upv.es
                Author notes
                [* ]Correspondence: ivangmg@ 123456unizar.es ; Tel.: +34-978-645-348
                Author information
                https://orcid.org/0000-0002-2726-6760
                https://orcid.org/0000-0002-4773-4904
                https://orcid.org/0000-0002-0862-0533
                Article
                Publisher ID: sensors-17-02606
                DOI: 10.3390/s17112606
                PMC ID: 5713010
                PubMed ID: 29137165
                SO-VID: b4185cec-f7c1-4ca1-bd7f-5ae1303f1cbd
                Copyright © © 2017 by the authors.
                License:

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                Date received : 12 October 2017
                Date accepted : 09 November 2017
                Categories
                Subject: Article

                ScienceOpen disciplines: Biomedical engineering
                Keywords: agent-based simulation,agent-based social simulation,multi-agent system,agent-oriented software engineering,underwater sensor,underwater sensor network,simulator software,fish measurement
                Data availability:
                ScienceOpen disciplines: Biomedical engineering
                Keywords: agent-based simulation, agent-based social simulation, multi-agent system, agent-oriented software engineering, underwater sensor, underwater sensor network, simulator software, fish measurement

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