Utilization of Departmental Computing GRID System for Development of an Artificial Intelligent Tapping Inspection Method, Tapping Sound Analysis

Author(s):  
Seung Jo Kim ◽  
Joon-Seok Hwang ◽  
Chang Sung Lee ◽  
Sangsan Lee
Author(s):  
Jin Woo Park ◽  
Si Hyoung Park ◽  
In Seong Hwang ◽  
Ji Joong Moon ◽  
Youngha Yoon ◽  
...  

2018 ◽  
Vol 1 (1) ◽  
pp. 2-19
Author(s):  
Mahmood Sh. Majeed ◽  
Raid W. Daoud

A new method proposed in this paper to compute the fitness in Genetic Algorithms (GAs). In this new method the number of regions, which assigned for the population, divides the time. The fitness computation here differ from the previous methods, by compute it for each portion of the population as first pass, then the second pass begin to compute the fitness for population that lye in the portion which have bigger fitness value. The crossover and mutation and other GAs operator will do its work only for biggest fitness portion of the population. In this method, we can get a suitable and accurate group of proper solution for indexed profile of the photonic crystal fiber (PCF).


2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Wanda Aulya ◽  
Fadhliani Fadhliani ◽  
Vivi Mardina

Water is the main source for life and also the most severe substance caused by pollution. The mandatory parameters for determining microbiological quality of drinking water are total non-fecal Coliform bacteria and Coliform fecal (Escherichia coli). Coliform bacteria are a group of microorganisms commonly used as indicators, where these bacteria can be a signal to determine whether a water source has been contaminated by bacteria or not, while fecal Coliform bacteria are indicator bacteria polluting pathogenic bacteria originating from human feces and warm-blooded animals (mammals) . The water inspection method in this study uses the MPN (Most Probable Number) method which consists of 3 tests, namely, the presumption test, the affirmation test, and the reinforcement test. The results showed that of 15 drinking water samples 8 samples were tested positive for Coliform bacteria with the highest total bacterial value of sample number 1, 15 (210/100 ml), while 7 other samples were negative. From 8 positive Coliform samples only 1 sample was stated to be negative fecal Coliform bacteria and 7 other samples were positive for Coliform fecal bacteria with the highest total bacterial value of sample number 1 (210/100 ml).


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