scholarly journals Harmonizing Multi-Source Sonar Backscatter Datasets for Seabed Mapping Using Bulk Shift Approaches

2020 ◽  
Vol 12 (4) ◽  
pp. 601 ◽  
Author(s):  
Benjamin Misiuk ◽  
Craig J. Brown ◽  
Katleen Robert ◽  
Myriam Lacharité

The development of multibeam echosounders (MBES) as a seabed mapping tool has resulted in the widespread uptake of backscatter intensity as an indicator of seabed substrate properties. Though increasingly common, the lack of standard calibration and the characteristics of individual sonars generally produce backscatter measurements that are relative to a given survey, presenting major challenges for seabed mapping in areas that comprise multiple MBES surveys. Here, we explore methods for backscatter dataset harmonization that leverage areas of mutual overlap between surveys for relative statistical calibration—referred to as “bulk shift” approaches. We use three multispectral MBES datasets to simulate the harmonization of backscatter collected over multiple years, and using multiple operating frequencies. Results suggest that relatively simple statistical models are adequate for bulk shift harmonization procedures, and that more flexible approaches may produce inconsistent results that risk statistical overfitting. While harmonizing datasets collected using the same operating frequency from separate surveys is generally feasible given reasonable temporal limitations, results suggest that the success at harmonizing datasets of different operating frequencies partly depends on the extent to which the frequencies differ. We recommend approaches and diagnostics for ensuring the quality of harmonized backscatter mosaics, and provide an R function for implementing the methods presented here.

2014 ◽  
Vol 28 (4) ◽  
pp. 869-887 ◽  
Author(s):  
Paul F. Williams

SYNOPSIS In this brief paper, I provide an argument that the rigor that allegedly characterizes contemporary mainstream accounting research is a myth. Expanding on arguments provided by West (2003), Gillies (2004), and Williams (1989), I show that the numbers utilized extensively to construct the statistical models that are the central defining feature of rigorous accounting research are, in many cases, not adequate to the task. These numbers are operational numbers that cannot be construed as measures or quantities of any kind of stable property. Constructing elaborate calculative models using operational numbers leads to equations whose results are not clearly decipherable. The rigorous nature of certain preferred forms of accounting research is, thus, largely a matter of appearance and not a substantive quality of the research mode that we habitually label “rigorous.” Thus, the policy recommendations implied by the results of rigorous accounting research may be viewed with considerable skepticism.


2020 ◽  
Vol 2 (1) ◽  
pp. 1-6
Author(s):  
A Nugraha ◽  
I Syarif ◽  
F. R. Saputra

The purpose of this study was to determine the increase in welfare of beef cattle production sharing systems. Data collection time is from January to February 2020. The research was conducted in Kulo Subdistrict, Sidenreng Rappang District, Survey Research Methodology. A sample of 64 farmers was taken (total sampling). Data analysis method is testing statistical models using SEM SmartPLS (Partial Least Square) 2.0. The results of the study explained that the Improvement of Beef Cattle Farmers' Welfare Sharing in the District of Kulo could be done with strategies to improve the aspects of individual farmers, improve stakeholder relations, and improve the quality of farmers. 


Author(s):  
Peter Croft ◽  
Richard D Riley ◽  
Karel GM Moons ◽  
Harry Hemingway

This chapter introduces the PROGRESS framework, which describes four types of prognosis research, each addressing different questions. The four types concern: studies of overall prognosis (the average outcome, or outcome risk, in people with a particular health condition, in the context of the nature and quality of current care); prognostic factors (characteristics associated with changes in the average outcome, or outcome risk, across individuals); prognostic models (development, validation, and impact evaluation of statistical models, incorporating multiple prognostic factors for use in clinical practice to predict an individual’s outcome value or to estimate their outcome risk); and predictors of treatment effect (characteristics that predict whether an individual responds to a particular treatment or not). Examples of each type are given to illustrate the framework.


2021 ◽  
pp. 129-148
Author(s):  
Jana Apiar ◽  
Peter Apiar

The subject of the presented study is taken from a dissertation project by one of the authors who focused on the processing of archaeobotanical assemblages from the Roman Period. The main aim of the research was the reconstruction of selected aspects of the subsistence strategy of the population in the given period based on the evaluation of archaeobotanical data from various chronological and cultural contexts in a designated region, available to author. The analysed sets were obtained during field excavations primarily conducted in the last third of the 20th century and the beginning of the 21st century. Uniform methods of archaeobotanical sampling were not applied in the acquisition of these assemblages. Source information on the origin of the samples was considerably heterogeneous and, in many cases, distinctly fragmentary. This was the impulse behind the investigation into the question as to whether, and to what extent, the method of sampling affects the interpretive value of the investigated dataset and what are the limitations of the analysis of such a dataset. The principal aim of this study is not the archaeobotanical evaluation of samples, but rather to investigate a possible effect of their formal properties on the composition of archaeobotanical finds. The formal properties studied include the volume and the number of collected samples, and the spatial stratification of samples (context/feature). Intuitively, it would appear that the heterogeneous quality of this information may have a certain impact on the interpretive value of an archaeobotanical assemblage. We discuss the effect of the chosen method of sampling on the composition of macro-remains in archaeobotanical samples and assemblages with the use of statistical models.


2016 ◽  
Author(s):  
A. Younes ◽  
T. A. Mara ◽  
M. Fahs ◽  
O. Grunenberger ◽  
Ph. Ackerer

Abstract. In the present work, we study the quality of the statistical calibration of hydraulic and transport soil properties using an infiltration experiment in which, over a given period, tracer-contaminated water is injected into a laboratory column filled with a homogeneous soil. The numerical model is based on the Richards' equation for solving water flow and the advection-dispersion equation for solving solute transport. Several state variables (e.g., water content, solute concentration, pressure head) are measured during the experiment. Statistical calibration of the computer model is then carried out for different data sets and injection scenarios with the DREAM(ZS) Markov Chain Monte Carlo sampler. The results show that the injection period has a significant effect on the quality of the estimation, in particular, the posterior uncertainty range. The hydraulic and transport parameters of the investigated soil can be estimated from the infiltration experiment using the concentration and cumulative outflow, which are measured non-intrusively. A significant improvement of the identifiability of the parameters is observed when the pressure data from measurements taken inside the column are also considered in the inversion.


Author(s):  
Antonio Laverghetta Jr. ◽  
John Licato

The age at which children acquire words is an important psycholinguistic property for modeling the growth of children's semantic networks. Much work over the years has explored how to effectively exploit statistical models to predict the age at which a word will be acquired, ranging from simple linear regression to LSA and skip-gram. However, thus far no work has explored whether transformers are any better at modeling word acquisition, despite the superior performance they have achieved on a wide variety of natural language processing (NLP) benchmarks. In this paper, we explore using several transformer models to predict the age of acquisition norms for several datasets. We evaluate the quality of our models using various experiments based on prior work and compare the transformers against two baseline models. We obtain promising results overall, as the transformers can outperform the baselines in most cases.


1999 ◽  
Vol 42 (2) ◽  
pp. 139-148
Author(s):  
W. Wittmann ◽  
K.-U. Götz ◽  
W. Peschke ◽  
J.-P. Lindner ◽  
M. Hause

Abstract. Title of the paper: The influence of MHS-genotypes on fattening and carcass Performance traits of purebred Piétrain pigs and PI x DL slaughter pigs at testing station For the comparison of fattening and carcass performance traits as well as the meat quality of different MHSgenotypes, one Pietrain group with 434 and another one of 64 PI x DL animals of both sexes were evaluated. The LSQ-means from an animal model showed in tendency a lower fattening Performance of the stresssusceptible genotypes. Significant differences were found for higher fat layers and fat surfaces and for lower meat surfaces and percentage of lean meat in NP- and NN-genotypes as compared to the PP-animals. The differences between the MHS-genotypes of the PI x DL animals were similar to those of the Pietrain animals. Both Statistical models confirmed a better meat quality already in the NP-genotypes. With respect to lower loss rates, reduction of insufficient meat qualities (PSE, DFD) and a still high proportion of lean meat of the NP- and NN- animals, a selection ofthe Pidtrain race for stress-resistance should be suitable.


Author(s):  
Jim Morey ◽  
Gary Scherzer ◽  
Hoseoup Lee

<p class="MsoNormal" style="text-align: justify; margin: 0in 34.2pt 0pt 0.5in;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Seventy-three New York hospitals were examined to determine if a relationship between age of assets, fiscal viability and quality of care existed.<span style="mso-spacerun: yes;">&nbsp; </span>These factors were examined for 2002 for each of the hospitals selected.<span style="mso-spacerun: yes;">&nbsp; </span>Several financial variables were used to construct a fiscal viability index; and a quality index was created from selected mortality outcomes and procedural measures that may be used to measure specific aspects of institutional care.<span style="mso-spacerun: yes;">&nbsp; </span>The premise that age of assets and fiscal viability will influence quality is gleaned from the Donabedian Model in which he proposed three domains important to the quality of health care.<span style="mso-spacerun: yes;">&nbsp; </span>Utilizing both the financial and quality of care indices, the following statistical models were prepared: Effect of asset age on fiscal viability index, Effect of asset age on individual fiscal viability measures, and Effect of asset age and fiscal viability index on quality index<span style="mso-spacerun: yes;">&nbsp; </span></span></span></p>


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