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1. |
Record Nr. |
UNINA9910210259103321 |
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Autore |
Gabetti, Roberto |
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Titolo |
Torino Piemonte Architetti / Roberto Gabetti ; scritti scelti a cura di Sisto Giriodi |
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ISBN |
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Descrizione fisica |
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Locazione |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNINA9910464602703321 |
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Titolo |
Fishing vessel execution of acoustic surveys for deep-sea species : main issues and way forward |
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Pubbl/distr/stampa |
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Rome : , : Food and Agriculture Organization of the United Nations, , 2012 |
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Descrizione fisica |
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1 online resource (105 p.) |
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Collana |
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FAO fisheries and aquaculture circular, , 2070-6065 ; ; no. 1059 |
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Soggetti |
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Underwater acoustics |
Fishing surveys |
Fishery resources |
Fish stock assessment |
Electronic books. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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""PREPARATION OF THIS DOCUMENT""; ""ABSTRACT""; ""CONTENTS""; ""1. INTRODUCTION AND BACKGROUND""; ""1.1 Introduction""; ""1.2 Background""; ""2. INSTITUTIONAL AND ORGANIZATIONAL ISSUES""; ""2.1 Who this report is intended for""; ""2.2 Why there is an issue""; ""2.3 Strategic and tactical considerations""; ""2.4 Requirements that must be met for stock assessment""; ""3. APPLICATIONS AT SEA AND OPERATIONAL CHALLENGES""; ""3.1 Operational characteristics""; ""3.2 Role of incentives/disincentives""; ""3.3 Integrating surveys with commercial fishing activities""; ""3.4 Echo mark identification"" |
""4. VESSELS AND EQUIPMENT""""4.1 Introduction""; ""4.2 The echosounder""; ""4.3 Frequency considerations""; ""4.4 Choice of vessel""; ""4.5 Location of transducers""; ""4.6 Calibration""; ""4.7 Opportunities for introduction of new technologies""; ""5. SURVEY METHODS""; ""5.1 Strategic considerations""; ""5.3 Area-based surveys""; ""5.4 Multiple surveys""; ""5.5 Deciding which data to use for estimation of abundance""; ""6. ACOUSTIC DATA PROCESSING""; ""7. ACOUSTIC BACKSCATTERING CROSS-SECTION VALUES""; ""7.1 Importance of proper specification"" |
""7.2 Problems associated with use of Ï?b and sv values""""8. ESTIMATION OF ABUNDANCE""; ""8.1 Introduction""; ""8.2 Area-based surveys""; ""8.3 Aggregation-based surveys""; ""8.4 Comparison of estimators""; ""9. UNCERTAINTY OF RESULTS""; ""9.1 Sources of uncertainty""; ""9.2 Sampling error""; ""9.3 Determination of species composition""; ""9.4 Backscattering cross-section""; ""9.5 Fish distribution and behaviour""; ""9.6 Weather""; ""9.7 Seafloor acoustic “dead zoneâ€?""; ""9.8 Calibration error""; ""9.9 Other errors""; ""10. IMPORTANCE OF COLLECTION OF BIOLOGICAL DATA"" |
""10.1 Data to be collected""""10.2 Species composition of the catch""; ""10.3 Length and weight frequency data""; ""10.4 Records of bycatch""; ""10.5 Sex composition and status of gonads""; ""10.6 Otoliths""; ""11. INCORPORATING INDUSTRY SURVEY RESULTS INTO THE ASSESSMENT AND MANAGEMENT PROCESS""; ""11.1 Stock assessment""; ""11.2 Indices of abundance""; ""11.3 Fishing vessel data and stock assessments""; ""12. FUNDING OF ACOUSTIC SURVEYS""; ""12.1 Funding considerations""; ""12.2 Cost items""; ""12.3 National applications""; ""13. DISCUSSION""; ""13.1 Common views"" |
""13.2 Communication with vessel crews""""13.3 Research strategies""; ""14. WORKSHOP RECOMMENDATIONS""; ""14.1 General recommendations""; ""14.2 Applications at sea and operational challenges""; ""14.3 Vessels and equipment""; ""14.4 Operational protocols""; ""14.5 Collection of biological data""; ""14.6 Acoustic data processing""; ""14.7 Estimating and estimates of acoustic backscattering values of deepwater species""; ""14.8 Estimation of abundance""; ""14.9 Uncertainty (error in estimates)""; ""14.10 Costs involved in commercial vessel stock assessment and funding issues"" |
""15. REFERENCES"" |
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3. |
Record Nr. |
UNINA9910484827803321 |
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Autore |
Owsiński Jan W |
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Titolo |
Data Analysis in Bi-partial Perspective: Clustering and Beyond / / by Jan W. Owsiński |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (XIX, 153 p.) |
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Collana |
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Studies in Computational Intelligence, , 1860-949X ; ; 818 |
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Disciplina |
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Soggetti |
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Engineering—Data processing |
Computational intelligence |
Artificial intelligence |
Data Engineering |
Computational Intelligence |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Preface -- Chapter 1. Notation and main assumptions -- Chapter 2. The problem of cluster analysis -- Chapter 3. The general formulation of the objective function -- Chapter 4. Formulations and rationales for other problems in data analysis, etc. |
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Sommario/riassunto |
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This book presents the bi-partial approach to data analysis, which is both uniquely general and enables the development of techniques for many data analysis problems, including related models and algorithms. It is based on adequate representation of the essential clustering problem: to group together the similar, and to separate the dissimilar. This leads to a general objective function and subsequently to a broad class of concrete implementations. Using this basis, a suboptimising procedure can be developed, together with a variety of implementations. This procedure has a striking affinity with the classical hierarchical merger algorithms, while also incorporating the stopping rule, based on the objective function. The approach resolves the cluster number issue, as the solutions obtained include both the content and the number of clusters. Further, it is demonstrated how the |
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bi-partial principle can be effectively applied to a wide variety of problems in data analysis. The book offers a valuable resource for all data scientists who wish to broaden their perspective on basic approaches and essential problems, and to thus find answers to questions that are often overlooked or have yet to be solved convincingly. It is also intended for graduate students in the computer and data sciences, and will complement their knowledge and skills with fresh insights on problems that are otherwise treated in the standard “academic” manner. |
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