Welding - Grouping systems for materials - European materials

2021 ◽  
Keyword(s):  
Grouping Systems

O197 Clinical staging of oropharyngeal carcinoma – evaluation of stage grouping systems

2007 ◽  
Vol 2 (1) ◽  
pp. 129
Author(s):  
L.P. Kowalski ◽  
P. Pedruzzi ◽  
B. Valdecir ◽  
G. Ramos ◽  
A. Sanabria ◽  
...  
Keyword(s):  
Clinical Staging ◽  
Oropharyngeal Carcinoma ◽  
Stage Grouping ◽  
Grouping Systems

scholarly journals AI Proposition for Crypt Information Management with Maximized EM Modelling

2019 ◽  
Vol 9 (2) ◽  
pp. 1287-1291
Keyword(s):  
Information Management ◽  
Cutting Edge ◽  
Achievement Rate ◽  
Present Information ◽  
Grouping Systems

There are a few circumstances where we utilize cutting edge innovations to recognize another element from the information we have. Regardless of whether it might be finished data or halfway data we attempt to recognize the new thing from the information. Mysterious information is such we have to concentrate on estimating the situations of achievement rate with this sort of enigmatic information which resembles a futile information. Enigmatic esteem resembles a pointless information which resembled an old information. We have to refine that information which isn't certified at that time. For instance consider age in an informational index as the enigmatic information since when that informational index was made that client might be with some age and after such a significant number of years still the age will be continue as before in the dataset with no update. This sort of data can be handled utilizing the grouping instrument which can be distinguished dependent on the data we accumulated from the store. The usefulness referenced in this article is to quantify the enigmatic information with the AI and approving the model dependent on the exactness we scored with the present information accessible. The total article talks about the activities we perform to accomplish the exactness of the model with various grouping systems.

scholarly journals PENGELOMPOKAN KEJADIAN GEMPA BUMI MENGGUNAKAN FUZZY C-MEANS CLUSTERING

2019 ◽  
Vol 4 (2) ◽  
pp. 103-110
Author(s):  
Ryan Rifqi Arista ◽  
Rosa Andrie Asmara ◽  
Dwi Puspitasari
Keyword(s):  
Eurasian Plate ◽  
Tectonic Plates ◽  
Fuzzy C Means ◽  
Australian Plate ◽  
The Pacific ◽  
Earthquake Vulnerability ◽  
Fuzzy C Means Clustering ◽  
Grouping Systems ◽  
Two Parameters ◽  
High Level

The Indonesian region has a high level of earthquake vulnerability when compared to other countries. This is because Indonesia's position is at the confluence of three large tectonic plates namely the Eurasian plate, the Indo-Australian plate, and the Pacific plate. The high level of earthquake susceptibility is evidenced by significant earthquake data from 2005 to 2009, which recorded 26 significant earthquakes over a period of 4.8 to 8.6 on the Richter scale. The earthquake also caused impacts including casualties, injuries, damage to houses and destruction of houses.The earthquake event grouping system is a system that functions to classify earthquake events based on two main parameters, namely earthquake strength parameters and earthquake impact parameters. The two parameters are grouped separately, so that the grouping process produces two kinds of grouping results. The stages of this system start from preprocessing data to eliminate noise, then take grouping parameters from the user in the form of the number of clusters, minimum error values, and the maximum iteration limit. Grouping is done using fuzzy c-means method. The grouping results are then displayed in table form and in the form of coordinates in Google Maps.The grouping of earthquake events has been tested by comparing the results of grouping systems with the results of manual grouping. Testing is done by inputting a number of different maximum iterations. Based on the test results it was found that the greater the maximum iteration value will affect the accuracy of grouping.

scholarly journals Can bryophyte groups increase functional resolution in tundra ecosystems?

2021 ◽  
Author(s):  
Signe Lett ◽  
Ingibjörg Svala Jónsdóttir ◽  
Antoine Becker-Scarpitta ◽  
Casper T. Christiansen ◽  
Heinjo During ◽  
...  
Keyword(s):  
Functional Groups ◽  
Functional Group ◽  
Environmental Changes ◽  
Intraspecific Variability ◽  
Water Holding Capacity ◽  
Plant Functional Groups ◽  
Relative Contribution ◽  
Grouping Systems ◽  
Water Holding ◽  
Tundra Ecosystems

The relative contribution of bryophytes to plant diversity, primary productivity, and ecosystem functioning increases towards colder climates. Bryophytes respond to environmental changes at the species level, but because bryophyte species are relatively difficult to identify, they are often lumped into one functional group. Consequently, bryophyte function remains poorly resolved. Here, we explore how higher resolution of bryophyte functional diversity can be encouraged and implemented in tundra ecological studies. We briefly review previous bryophyte functional classifications and the roles of bryophytes in tundra ecosystems and their susceptibility to environmental change. Based on shoot morphology and colony organization, we then propose twelve easily distinguishable bryophyte functional groups. To illustrate how bryophyte functional groups can help elucidate variation in bryophyte effects and responses, we compiled existing data on water holding capacity, a key bryophyte trait. Although plant functional groups, can mask potentially high inter- and intraspecific variability, we found better separation of bryophyte functional group means compared to previous grouping systems regarding water holding capacity. This suggests that our bryophyte functional groups truly represent variation in the functional roles of bryophytes in tundra ecosystems. Lastly, we provide recommendations to improve monitoring of bryophyte community changes in tundra study sites.

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