scholarly journals Statistical analysis of simulation output: State of the art

Author(s):  
Christos Alexopoulos
2021 ◽  
Author(s):  
Miguel D. Fernández-de-Bobadilla ◽  
Alba Talavera-Rodríguez ◽  
Lucía Chacón ◽  
Fernando Baquero ◽  
Teresa M. Coque ◽  
...  

AbstractMotivationComparative genomics is a growing field but one that will be eventually overtaken by sample size studies and the increase of available genomes in public databases. We present the Pangenome Analysis Toolkit (PATO) designed to simultaneously analyze thousands of genomes using a desktop computer. The tool performs common tasks of pangenome analysis such as core-genome definition and accessory genome properties and includes new features that help characterize population structure, annotate pathogenic features and create gene sharedness networks. PATO has been developed in R to integrate with the large set of tools available for genetic, phylogenetic and statistical analysis in this environment.ResultsPATO can perform the most demanding bioinformatic analyses in minutes with an accuracy comparable to state-of-the-art software but 20–30x times faster. PATO also integrates all the necessary functions for the complete analysis of the most common objectives in microbiology studies. Lastly, PATO includes the necessary tools for visualizing the results and can be integrated with other analytical packages available in R.AvailabilityThe source code for PATO is freely available at https://github.com/irycisBioinfo/PATO under the GPLv3 [email protected] informationSupplementary data are available at Bioinformatics online


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Yi-Hui Qiu ◽  
Xin Yang ◽  
Zong-Ze Li ◽  
Chiyu Zhang ◽  
Shui-Xuan Chen

Abstract Artificial intelligence (AI) technology has been widely applied in various fields in recent years. Nevertheless, no systematic study has yet been conducted on the effects of AI technology on different fields. In this study, the impacts of the latest AI technology on technological innovation in different fields were analysed and quantized systematically from a patent perspective. Moreover, trends on AI technological innovation in some fields were analysed thoroughly. We conducted this study on a dataset of patents related to AI technology. Based on the patent dataset, we carried out a statistical analysis on technology fields, which we defined and classified based on international patent classification (IPC) number. Distributions of IPC in different fields were also analysed to determine the trends on AI technological innovation. The research conclusions can provide useful information to investors and enterprises, who are interested in the state of the art concerning AI technology.


2020 ◽  
Vol 81 (12) ◽  
pp. 2471-2487 ◽  
Author(s):  
Simone Malutta ◽  
Masato Kobiyama ◽  
Pedro Luiz Borges Chaffe ◽  
Nadia Bernardi Bonumá

Abstract This work is a review of the use of hysteresis to quantify sediment discharge dynamics. We reviewed 71 journal articles from the year 1953 to the present day focusing on two topics: the factors that influence hysteresis; and hysteresis quantification. The main factors influencing hysteresis are: (a) magnitude and sequence of events; (b) sediment particle size distribution; (c) basin size; and (d) land use and sediment source. Hysteresis quantification can be done using several different methods that can be grouped as: (a) hysteresis indexes; (b) statistical analysis; and (c) uncertainty analysis. Most studies were conducted in Western Europe and the USA. The studies, in general, show how the factors listed above influence the shape and patterns of hysteresis. However, the sediment dynamics are complex, and the hysteresis patterns may be linked to many other factors, such as slope and drainage systems. The quantification of hysteresis still appears, mainly with the hysteresis index and statistical analysis. Therefore, there are still many other factors that influence hysteresis patterns, as well as hysteresis rates and uncertainty analyses.


Author(s):  
Lyuben D. Ivanov ◽  
Ge Wang

This paper analyzes the state-of-the-art concerning this subject. The objectives are: 1) to provide data of still water bending moments and shear forces that were collected from loading manuals of dozens of tankers 2) conduct statistical analysis of the loading cases and 3) discuss possible ways for further improvement of knowledge about the variability of still water loads during real ships’ operation.


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