2017 Ventenata dubia distribution - probability

2021 ◽  
Author(s):  
Ty C. Nietupski ◽  
Becky K. Kerns
Keyword(s):  
Distribution Probability

“The Crooked Smile of TCR”: Banks’ Solvency and Restructuring Costs in the European Banking Industry

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110459
Author(s):  
Małgorzata Iwanicz-Drozdowska ◽  
Krzysztof Jackowicz ◽  
Maciej Karczmarczyk
Keyword(s):  
Probability Function ◽  
Bank Failure ◽  
Capital Adequacy ◽  
Special Importance ◽  
Stress Tests ◽  
Distribution Probability ◽  
Total Capital ◽  
European Banking ◽  
European Banks ◽  
Bank Restructuring

In this study, we analyze the probability of bank failure, the expected losses, and the costs of bank restructuring with the application of a lognormal distribution probability function for three categories of European banks, that is, small, medium, and large, over the post-crisis period from 2012 to 2016. Our goal was to determine whether the total capital ratio (TCR) properly reflects banks’ solvency under stress conditions. We identified a phenomenon that one can call the “crooked smile of TCR”. Medium-sized banks with relatively high TCRs performed poorly in stress tests; however, the probability of bank failure increases slightly with the size of the bank, while the TCR decreases. We claim that the focus on capital adequacy measures is not sufficient to achieve the goal of improving banks’ stability and reducing their restructuring costs. Our results are of special importance for medium-sized banks, as these banks are not regularly subjected to publicly available stress tests.

scholarly journals Bootstrapping Bloch bands

2021 ◽  
Author(s):  
Serguei Tchoumakov ◽  
Serge Florens
Keyword(s):  
Search Space ◽  
Quantum Field Theories ◽  
New Techniques ◽  
Bootstrap Methods ◽  
Quantum Operator ◽  
Canonical Variables ◽  
Distribution Probability ◽  
Anharmonic Potential ◽  
Bloch Band ◽  
Band Spectra

Abstract Bootstrap methods, initially developed for solving statistical and quantum field theories, have recently been shown to capture the discrete spectrum of quantum mechanical problems, such as the single particle Schrödinger equation with an anharmonic potential. The core of bootstrap methods builds on exact recursion relations of arbitrary moments of some quantum operator and the use of an adequate set of positivity criteria. We extend this methodology to models with continuous Bloch band spectra, by considering a single quantum particle in a periodic cosine potential. We find that the band structure can be obtained accurately provided the bootstrap uses moments involving both position and momentum variables. We also introduce several new techniques that can apply generally to other bootstrap studies. First, we devise a trick to reduce by one unit the dimensionality of the search space for the variables parametrizing the bootstrap. Second, we employ statistical techniques to reconstruct the distribution probability allowing to compute observables that are analytic functions of the canonical variables. This method is used to extract the Bloch momentum, a quantity that is not readily available from the bootstrap recursion itself.

scholarly journals Steganalysis of Quantization Index Modulation Steganography in G.723.1 Codec

2020 ◽  
Vol 12 (1) ◽  
pp. 17
Author(s):  
Zhijun Wu ◽  
Rong Li ◽  
Panpan Yin ◽  
Changliang Li
Keyword(s):  
Transition Probability ◽  
Principal Component ◽  
Transition Probability Matrix ◽  
Support Vector ◽  
Quantization Index Modulation ◽  
Distribution Probability ◽  
Before And After ◽  
Security Of Network ◽  
Index Value ◽  
Index Modulation

Steganalysis is used for preventing the illegal use of steganography to ensure the security of network communication through detecting whether or not secret information is hidden in the carrier. This paper presents an approach to detect the quantization index modulation (QIM) of steganography in G.723.1 based on the analysis of the probability of occurrence of index values before and after steganography and studying the influence of adjacent index values in voice over internet protocol (VoIP). According to the change of index value distribution characteristics, this approach extracts the distribution probability matrix and the transition probability matrix as feature vectors, and uses principal component analysis (PCA) to reduce the dimensionality. Through a large amount of sample training, the support vector machine (SVM) is designed as a classifier to detect the QIM steganography. The speech samples with different embedding rates and different durations were tested to verify their impact on the accuracy of the steganalysis. The experimental results show that the proposed approach improves the accuracy and reliability of the steganalysis.

Mean Shift-Based Target Tracking for Moving Spherical Object in Video

2014 ◽  
Vol 623 ◽  
pp. 156-160
Author(s):  
Bo Zhao Li
Keyword(s):  
Target Tracking ◽  
Mean Shift ◽  
Feature Points ◽  
Color Information ◽  
Spherical Object ◽  
Color Feature ◽  
Color Distribution ◽  
Distribution Probability ◽  
Flow Algorithm ◽  
Tracking Object

When researching on target tracking in the on or off line video, using a variety of methods such as MeanShift, Camshaft’s, feature points and optical flow algorithm. MeanShift target tracking algorithm is introduced in this paper. Firstly, tracking object is selected by human-computer interaction. Then color feature histogram is obtained using RGB color information, and color distribution probability image is got by converting color feature histogram. Finally, by comparing the probability difference of color distribution of the adjacent frames, motion directions of the object’s center are obtained, which object can be effectively tracked.

Exact distribution of word occurrences in a random sequence of letters

1999 ◽  
Vol 36 (01) ◽  
pp. 179-193 ◽  
Author(s):  
S. Robin ◽  
J. J. Daudin
Keyword(s):  
Distribution Function ◽  
Sequence Analysis ◽  
Cumulative Distribution Function ◽  
Counting Process ◽  
Random Sequence ◽  
Exact Distribution ◽  
Cumulative Distribution ◽  
Longitudinal Distribution ◽  
Genome Sequence Analysis ◽  
Distribution Probability

The study of the distribution of the distance between words in a random sequence of letters is interesting in view of application in genome sequence analysis. In this paper we give the exact distribution probability and cumulative distribution function of the distances between two successive occurrences of a given word and between the nth and the (n+m)th occurrences under three models of generation of the letters: i.i.d. with the same probability for each letter, i.i.d. with different probabilities and Markov process. The generating function and the first two moments are also given. The point of studying the distances instead of the counting process is that we get some knowledge not only about the frequency of a word but also about its longitudinal distribution in the sequence.

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