Interval inversion of well-logging data for automatic determination of formation boundaries by using a float-encoded genetic algorithm

A method for the determination of crystal structures from powder diffraction data is presented that circumvents the difficulties associated with separate indexing. For the simultaneous optimization of the parameters that describe a crystal structure a genetic algorithm is used together with a pattern matching technique based on auto and cross correlation functions.<br>

Download Full-text

Automatic Determination of Optimal FIB Operations for Improved Circuit Probing and Fast Reconfiguration

ISTFA 2000: Conference Proceedings from the 26th International Symposium for Testing and Failure Analysis ◽

10.31399/asm.cp.istfa2000p0407 ◽

2000 ◽

Author(s):

Romain Desplats ◽

Timothee Dargnies ◽

Jean-Christophe Courrege ◽

Philippe Perdu ◽

Jean-Louis Noullet

Keyword(s):

Integrated Circuit ◽

Focused Ion Beam ◽

Ion Beam ◽

Semiconductor Devices ◽

Front Side ◽

Automatic Determination ◽

Metal Line ◽

New Approach ◽

Metal Layers

Abstract Focused Ion Beam (FIB) tools are widely used for Integrated Circuit (IC) debug and repair. With the increasing density of recent semiconductor devices, FIB operations are increasingly challenged, requiring access through 4 or more metal layers to reach a metal line of interest. In some cases, accessibility from the front side, through these metal layers, is so limited that backside FIB operations appear to be the most appropriate approach. The questions to be resolved before starting frontside or backside FIB operations on a device are: 1. Is it do-able, are the metal lines accessible? 2. What is the optimal positioning (e.g. accessing a metal 2 line is much faster and easier than digging down to a metal 6 line)? (for the backside) 3. What risk, time and cost are involved in FIB operations? In this paper, we will present a new approach, which allows the FIB user or designer to calculate the optimal FIB operation for debug and IC repair. It automatically selects the fastest and easiest milling and deposition FIB operations.

Download Full-text

Automatic Determination of Unbiased Luminosity Functions for H [CSC]ii[/CSC] Regions. II. Four Nearby Dwarf Galaxies

The Astronomical Journal ◽

10.1086/300577 ◽

1998 ◽

Vol 116 (5) ◽

pp. 2246-2262 ◽

Cited By ~ 7

Author(s):

Robin L. Kingsburgh ◽

Marshall L. McCall

Keyword(s):

Dwarf Galaxies ◽

Automatic Determination ◽

Luminosity Functions

Download Full-text

Full spectrum and genetic algorithm-selected spectrum-based chemometric methods for simultaneous determination of azilsartan medoxomil, chlorthalidone, and azilsartan: Development, validation, and application on commercial dosage form

Open Chemistry ◽

10.1515/chem-2021-0022 ◽

2021 ◽

Vol 19 (1) ◽

pp. 205-213

Author(s):

Hany W. Darwish ◽

Abdulrahman A. Al Majed ◽

Ibrahim A. Al-Suwaidan ◽

Ibrahim A. Darwish ◽

Ahmed H. Bakheit ◽

...

Keyword(s):

Genetic Algorithm ◽

Simultaneous Determination ◽

Predictive Power ◽

Principal Component Regression ◽

Selection Procedure ◽

Principal Component ◽

Chemometric Methods ◽

Full Spectrum ◽

Azilsartan Medoxomil

Abstract Five various chemometric methods were established for the simultaneous determination of azilsartan medoxomil (AZM) and chlorthalidone in the presence of azilsartan which is the core impurity of AZM. The full spectrum-based chemometric techniques, namely partial least squares (PLS), principal component regression, and artificial neural networks (ANN), were among the applied methods. Besides, the ANN and PLS were the other two methods that were extended by genetic algorithm procedure (GA-PLS and GA-ANN) as a wavelength selection procedure. The models were developed by applying a multilevel multifactor experimental design. The predictive power of the suggested models was evaluated through a validation set containing nine mixtures with different ratios of the three analytes. For the analysis of Edarbyclor® tablets, all the proposed procedures were applied and the best results were achieved in the case of ANN, GA-ANN, and GA-PLS methods. The findings of the three methods were revealed as the quantitative tool for the analysis of the three components without any intrusion from the co-formulated excipient and without prior separation procedures. Moreover, the GA impact on strengthening the predictive power of ANN- and PLS-based models was also highlighted.

Download Full-text