scholarly journals Proper filter usage to retrieve multiwords from the MEDLINE n-gram set: Reply to the Turki et al commentary “Enhancing filter-based parenthetic abbreviation extraction methods”

2020 ◽  
Author(s):  
Chris J Lu ◽  
Amanda Payne ◽  
James G Mork
Keyword(s):  
Extraction Methods ◽  
N Gram ◽  
Proper Filter

scholarly journals A Study on the Performance of Feature Extraction Methods According to the Size of N-Gram

2018 ◽  
Vol 7 (3.33) ◽  
pp. 23
Author(s):  
Young Man Kwon ◽  
Min Gu Son ◽  
Dong Keun Chung ◽  
Myung Jae Lim
Keyword(s):  
Feature Extraction ◽  
Malware Detection ◽  
Extraction Methods ◽  
Model Based ◽  
N Gram

In this paper, we studied the performance of feature extraction methods according to the size of N-gram for malware detection. The feature is extracted by three methods, using Opcode Only, both Opcode and API and API Only from PE file. We measure the performance of them indirectly with measuring the AUC score and accuracy of classifier. We did experiments with the different N size by using several classifiers such as DT, SVM, KNN and BNB classifiers. As a result, we got the conclusion as followings. If we use N-gram technique, we recommend Opcode Only method through our experiments. Also, the instance-based classifier KNN and DT among the model based classifier have good performance than SVM and BNB.  

The effect of different extraction methods on chemical composition profile and pharmacological activities of essential oils and hydrosols

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381
Author(s):  
F Ghavidel ◽  
MM Zarshenas ◽  
A Sakhteman ◽  
A Gholami ◽  
Y Ghasemi ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Essential Oils ◽  
Extraction Methods ◽  
Composition Profile ◽  
Pharmacological Activities

Characterization of dissolved organic matter (DOM) extracted from soils by hot water percolation (HWP)

2010 ◽  
Vol 59 (1) ◽  
pp. 99-108 ◽  
Author(s):  
M. Takács ◽  
Gy. Füleky
Keyword(s):  
Organic Matter ◽  
Humic Acid ◽  
Natural Organic Matter ◽  
Extraction Methods ◽  
Soil Samples ◽  
Hot Water ◽  
Soil Extracts ◽  
Water Percolation ◽  
Soil Humic Acid

The Hot Water Percolation (HWP) technique for preparing soil extracts has several advantages: it is easily carried out, fast, and several parameters can be measured from the same solution. The object of this study was to examine the possible use of HWP extracts for the characterization of soil organic matter. The HPLC-SEC chromatograms, UV-VIS and fluorescence properties of the HWP extracts were studied and the results were compared with those of the International Humic Substances Society (IHSS) Soil Humic Acid (HA), IHSS Soil Fulvic Acid (FA) and IHSS Suwannee Natural Organic Matter (NOM) standards as well as their HA counterparts isolated by traditional extraction methods from the original soil samples. The DOM of the HWP solution is probably a mixture of organic materials, which have some characteristics similar to the Soil FA fractions and NOM. The HWP extracted organic material can be studied and characterized using simple techniques, like UV-VIS and fluorescence spectroscopy.

New Feature Vectors using GFCC for Speaker Identification

2018 ◽  
Vol 6 (8) ◽  
pp. 243
Author(s):  
A. Nagesh
Keyword(s):  
Speaker Recognition ◽  
Speaker Identification ◽  
Signal To Noise Ratio ◽  
Main Idea ◽  
Extraction Methods ◽  
Identification System ◽  
Identification Performance ◽  
Feature Vectors ◽  
Overall Performance ◽  
New Feature

The feature vectors of speaker identification system plays a crucial role in the overall performance of the system. There are many new feature vectors extraction methods based on MFCC, but ultimately we want to maximize the performance of SID system.  The objective of this paper to derive Gammatone Frequency Cepstral Coefficients (GFCC) based a new set of feature vectors using Gaussian Mixer model (GMM) for speaker identification. The MFCC are the default feature vectors for speaker recognition, but they are not very robust at the presence of additive noise. The GFCC features in recent studies have shown very good robustness against noise and acoustic change. The main idea is  GFCC features based on GMM feature extraction is to improve the overall speaker identification performance in low signal to noise ratio (SNR) conditions.

A Review of Different Techniques of Age Estimation from Human Face

2018 ◽  
Vol 4 (10) ◽  
pp. 6
Author(s):  
Khemchandra Patel ◽  
Dr. Kamlesh Namdev
Keyword(s):  
Age Estimation ◽  
Real Life ◽  
Extraction Methods ◽  
Human Face ◽  
Age Changes ◽  
Missing Children ◽  
Different Types ◽  
Age Variation ◽  
Human Faces ◽  
Facial Age

Age changes cause major variations in the appearance of human faces. Due to many lifestyle factors, it is difficult to precisely predict how individuals may look with advancing years or how they looked with "retreating" years. This paper is a review of age variation methods and techniques, which is useful to capture wanted fugitives, finding missing children, updating employee databases, enhance powerful visual effect in film, television, gaming field. Currently there are many different methods available for age variation. Each has their own advantages and purpose. Because of its real life applications, researchers have shown great interest in automatic facial age estimation. In this paper, different age variation methods with their prospects are reviewed. This paper highlights latest methodologies and feature extraction methods used by researchers to estimate age. Different types of classifiers used in this domain have also been discussed.

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