Probabilistic model about the influence of the number of stirring conditions considered during a radiated susceptibility test

2020 ◽  
pp. 101-122
Author(s):  
Guillaume Andrieu
Keyword(s):  
Probabilistic Model ◽  
Susceptibility Test

Extraction and Phytochemicals Determination of Traditional Medicinal Plants for Anti-microbial Susceptibility Test

2020 ◽  
Vol 2020 ◽  
Author(s):  
Firew Admasu
Keyword(s):  
Antimicrobial Activity ◽  
Medicinal Plants ◽  
Traditional Medicine ◽  
Crude Extract ◽  
Susceptibility Test ◽  
Plant Sample ◽  
Traditional Medicinal Plants ◽  
Traditional Health Care ◽  
Susceptibility Tests

Abstract: The study were conducted at Dilla University, College of Natural Sciences, Biological Sciences laboratories. Background: Ethiopia is a country with many ethnic groups, cultures and beliefs which in turn have contributed to the high diversity of traditional health care knowledge and practices of traditional medicine from local growth plants, animals and minerals for various physical and mental disorders of human and livestock population that passed from generation to generation for centuries. Medicinal plants contributors to pharmaceutical, agricultural and food industries in the world. The use of medicinal plants in the industrialized societies has been traced to extraction and development of several drugs used in order to heel some diseases having inhibiting effect against pathogenic microorganism. Objective: The main objective of this study was Extraction and Phytochemicals determination of traditional medicinal plants for anti microbial susceptibility test. Methodology: The extraction and identification of some phytochemicals crude compound which used for antimicrobial susceptibility test from plant sample such as Ocimum lamiifolium (OL), Croton maerosth (Cm) and Ruta chalepesis (RC) were conducted. Plant samples are collected, powdered using mortal and pistil and extracted using ethanol and some susceptibility tests were performed to identify some phytochemicals compound. Result: The main result of Antimicrobial activity test showed that the crude extract of OL has the highest zone of inhibition. The highest yield of crude extract (38.21%) was obtained from Croton maerosth (CM) which followed by Ruta chalepesis (RC) (32.43%). However, the lowest yield (28.37%) was obtained from Oscpmum lamifolium (OL). Conclusion: Traditional Medicine is used by many people to managing numerous conditions; it’s accessible and effective on antimicrobial activity. Therefore, it plays a significant role by reducing life-threatening ailments of people and other animals.

Assessment and Analysis of Credit Risk with Using of Logical and Probabilistic Model

2002 ◽  
Author(s):  
Vassilij Karassev ◽  
Andrey Roukine ◽  
E.D. Dmitrievich Solojentsev
Keyword(s):  
Credit Risk ◽  
Probabilistic Model

scholarly journals Joint Semantic Synthesis and Morphological Analysis of the Derived Word

2018 ◽  
Vol 6 ◽  
pp. 33-48 ◽  
Author(s):  
Ryan Cotterell ◽  
Hinrich Schütze
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Probabilistic Model ◽  
Morphological Analysis ◽  
Semantic Representation ◽  
English Word ◽  
Word Formation ◽  
Additive Models ◽  
Segmentation Accuracy ◽  
Morphological Productivity

Much like sentences are composed of words, words themselves are composed of smaller units. For example, the English word questionably can be analyzed as question+ able+ ly. However, this structural decomposition of the word does not directly give us a semantic representation of the word’s meaning. Since morphology obeys the principle of compositionality, the semantics of the word can be systematically derived from the meaning of its parts. In this work, we propose a novel probabilistic model of word formation that captures both the analysis of a word w into its constituent segments and the synthesis of the meaning of w from the meanings of those segments. Our model jointly learns to segment words into morphemes and compose distributional semantic vectors of those morphemes. We experiment with the model on English CELEX data and German DErivBase (Zeller et al., 2013) data. We show that jointly modeling semantics increases both segmentation accuracy and morpheme F1 by between 3% and 5%. Additionally, we investigate different models of vector composition, showing that recurrent neural networks yield an improvement over simple additive models. Finally, we study the degree to which the representations correspond to a linguist’s notion of morphological productivity.

Sign in / Sign up

Export Citation Format

Share Document