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Purification and partial characterization of α-amylase from soybean (Glycine max)
Tripathi, Pallavi,Dwevedi, Alka,Kayastha, Arvind M. Kyung Hee Oriental Medicine Research Center 2004 Oriental pharmacy and experimental medicine Vol.4 No.4
An ${\alpha}-Amylase$ was purified to apparent homogeneity from germinating soybean seeds (Glycine max). Enzyme showed high specificity for starch. ${\alpha}-Amylase$ from soybean has optimum pH at 7.6 in the pH range 4.0-10.6. At this pH, the $K_m$ of starch was 2.63 mg/ml and the $V_{max}$ was equal to 52.6 mg/ml/min protein. Optimum temperature of the enzyme was found to be $55^{\circ}C,\;Q_{10}$ equal to 1.85 and energy of activation equal to 12 kcal/mol. Additives like, EDTA reduced the activity of ${\alpha}-amylase$ whereas PMSF enhanced the activity. ${\alpha}-Amylase$ was inhibited by several heavy metal ions.
Harish Garg,Nikunj Aggarwal,Alka Tripathi 원광대학교 기초자연과학연구소 2017 ANNALS OF FUZZY MATHEMATICS AND INFORMATICS Vol.13 No.6
The theme of this work is to investigate a new generalized parametric directed divergence measure for intuitionistic fuzzy sets. For it, the entire paper is divided into two folds. Firstly, a new measure has been presented by incorporating the idea of convex linear combinations of the degree of their membership functions. Some desirable properties of the proposed measure have been also investigated. Secondly, divergence measure based method for solving the decision making problem has been presented. A ranking of the different attributes is based on the proposed generalized divergence measure and the sensitivity analysis on the ranking of the system has been done based on the decision-making parameters. An illustrative examples have been studied to show that the proposed function is more reasonable in the decision-making process than other existing functions.
( Mukta Goyal ),( Divakar Yadav ),( Alka Tripathi ) 한국정보처리학회 2017 Journal of information processing systems Vol.13 No.1
In this paper, Atanassov`s intuitionistic fuzzy set theory is used to handle the uncertainty of students` knowledgeon domain concepts in an E-learning system. Their knowledge on these domain concepts has been collected from tests that were conducted during their learning phase. Atanassov`s intuitionistic fuzzy user model is proposed to deal with vagueness in the user`s knowledge description in domain concepts. The user model uses Atanassov`s intuitionistic fuzzy sets for knowledge representation and linguistic rules for updating the user model. The scores obtained by each student were collected in this model and the decision about the students` knowledge acquisition for each concept whether completely learned, completely known, partially known or completely unknown were placed into the information table. Finally, it has been found that the proposed scheme is more appropriate than the fuzzy scheme.
Goyal, Mukta,Yadav, Divakar,Tripathi, Alka Korea Information Processing Society 2017 Journal of information processing systems Vol.13 No.1
In this paper, Atanassov's intuitionistic fuzzy set theory is used to handle the uncertainty of students' knowledgeon domain concepts in an E-learning system. Their knowledge on these domain concepts has been collected from tests that were conducted during their learning phase. Atanassov's intuitionistic fuzzy user model is proposed to deal with vagueness in the user's knowledge description in domain concepts. The user model uses Atanassov's intuitionistic fuzzy sets for knowledge representation and linguistic rules for updating the user model. The scores obtained by each student were collected in this model and the decision about the students' knowledge acquisition for each concept whether completely learned, completely known, partially known or completely unknown were placed into the information table. Finally, it has been found that the proposed scheme is more appropriate than the fuzzy scheme.