Showing 3 results for Information Theory
M. Mozafari Lagha , S.sh. Arab, J. Zahiri ,
Volume 9, Issue 4 (12-2018)
Abstract
Aims: Information of the protein structure is essential to understand the protein functions. Flexibility is one of the most important characteristics related to protein functions. Knowledge about flexibility of the protein structures can be helpful to improve protein structure prediction and comprehend their function. This study was conducted with the aim of investigating the flexibility prediction of protein structures, using support vector machine.
Materials and Methods: In this study, a balanced dataset containing 95 proteins was used. The features used in the present study for modeling amino acids formed a 33-dimensional vector. Some of them were obtained by crawling a window with the length of 17 focusing on the target amino acid on the protein chain, and some were only related to the target amino acid. To define the flexibility factor, the characteristics based on the information derived from the two-dimensional angular variations was used. The information was calculated for each amino acid by considering the position of each amino acid alone and for the adjacent amino acid pairs in a seventeenth window, and the support vector machine method was used for prediction.
Findings: The accuracy was 73.1%, F-measure was 71%, precision was 73%, and sensitivity was 73.2%. Acceptable superiority of the proposed method was confirmed in comparison with the current methods. The angular representation of each protein was able to accurately demonstrate the 3D characteristics and properties of the protein structure.
Conclusion: The accuracy is 73.1%, F-measure is 71%, precision is 73%, and sensitivity is 73.2% and angular aspect is the best descriptor for flexibility prediction. Angular representation of each protein can accurately reflect the 3D characteristics and properties of the protein structure.
Volume 13, Issue 2 (7-2013)
Abstract
The measurement of multidimensional poverty in 22 districts of Tehran is the main goal of this research. Studying human deprivation regarding basic needs i.e. health, nutrition, education and political freedom seems essential due to existing shortcomings of income-based poverty measurement approach. Here, we measure multidimensional poverty in terms of four attributes (income, housing, education and public health) using information theory approach developed by Maasoumi and Logo(2006) model. First, we calculate single-dimensional poverty based on each attribute. Then, according to difference in levels of substitutability among attributes we measure the absolute poverty using aggregate poverty line approach. The results show that the poorest districts of Tehran are district 19 in terms of income approach and districts 19 and 17 in terms of education and housing, respectively. The worst situation regarding public health belongs to district 16. The highest and the lowest multidimensional poverty rate were observed in districts 4 and 1 respectively. Furthermore, if substitution coefficient among attributes increases, then the multidimensional poverty rate will decrease. About 63 percent of Tehran population is of relative deprivation.
Volume 15, Issue 3 (11-2011)
Abstract
Introduction of an Optimized Model for Fixed Assets Classification in the Balance Sheet
(Case Study: Alimentary Production Corporations in Tehran Stock Exchange)
Mohammad Ali Aghaei1, Malihe Moradi2
1- Associated Professor, Department of Accounting, Faculty of Management & Economy, Tarbiat Modares University, Tehran, Iran
2- M.A. Student in Accounting, Department of Accounting, Faculty of Management & Economy, Tarbiat Modares University, Tehran, Iran.
Received: 23 /5/2010 Accept: 9/3/2011
This research is an attempt to suggest a new financial statement analysis method. In this method, the value of accounting information in balance sheet is measured by information theory. Henry Thiel (1969), applying the information theory in accounting; offered a new thought in financial statement analysis. He measured the value of financial statement information by using entropy. Entropy is a logarithmic measure of the rate of transfer of information in a particular message or language. In this research, we attempted to measure the value of information in alimentary corporations’ balance sheet by using entropy and suggested a new method for optimizing fixed assets classification, which increases the information value of those balance sheets. The results showed that if firms present fixed assets information by detail in the balance sheet, the entropy of information will increase and the high value of transmitted information will improve decision making by users of financial statements.
