Measure Of Information Uncertainty Research Articles

ИНФОРМАЦИОННАЯ ХАРАКТЕРИСТИКА ПЕРВИЧНОЙ ПОЧКИ НА ЭТАПАХ ЭМБРИОГЕНЕЗА У СИРИЙСКОГО ХОМЯКА

The state of the system «primary kidney of a Syrian hamster» at the stages of embryonic development was studied. The informational characteristic of the complexity and organization of the morphological system «primary kidney» was carried out by calculating the indicators: informational maximum entropy (Нmax): (Нmax) = Iog2n, where n is the number of classes, informational entropy (Н), as a measure of information uncertainty according to Shannon’s formula Н = -∑Рi Log2Pi, where Р – volume fraction of tissue components of the primary kidney; information organization of the system (S): relative entropy (h), coeffi cient of relative organization of the system (or coeffi cient of redundancy) (R): R = (Hmax-H) / Hmax 100%. Based on the studies carried out, it was found that the entropy of the «primary kidney» system in embryos increases by the end of the 1st stage of the organ’s life cycle to 1.07 bit, at the 2nd stage it decreases to 0.80 bit, which is associated with an increase in the proportion of mesenchyme and its predominance. over other structural components. The redundancy ratio increases in the middle of stage 1, then decreases towards the beginning of stage 2, then from the middle of stage 2, the redundancy ratio increases until the end of stage 3, which is associated with an increase in the stability of the system. The relative entropy during the observation period decreases from 52.54% at the beginning of stage 1 of the organ’s life cycle to 39.93% at stage 3.

Determining the number of redundant elements of the distribution network in compliance with the specified amount of information entropy

A mathematical economic model for searching an optimal solution is proposed. In addition, a measure of information uncertainty is proposed to solve the problem the construction of a distribution network structure with the redundancy. In the model, there is an objective function for searching minimum costs and the equations for determining an information entropy of operable and non-operable states of the distribution network. The equations are based on the approaches of Ralph Hartley and Claude Shannon for entropy determination. An important place in the mathematical model is the process of constructing of a constraint function to search an optimal solution. The right part of constraints is entropy, its value reflects requirements to provide the required reliability level of power supply of the consumer. The left part is used to determine the connection entropy between an energy source and the consumer. An example of determining the number of redundant elements is offered.

Cross Entropy for Discrete Z-numbers and Its Application in Multi-Criteria Decision-Making

Decisions are based on information, and the reliability of information affects the quality of decision-making. Z-number, produced by Zadeh, considers the fuzzy restriction and the reliability restriction of decision information simultaneously. Many scholars have conducted in-depth research on Z-number, and the concept has great application potential in the field of economic management. However, certain problems with the basic operations of Z-number still exist. Entropy is a measure of information uncertainty, and research on entropy and Z-number continues to be rare. This study initially defines the cross entropy of fuzzy restriction and that of the reliability of Z-numbers. On this basis, a comprehensive weighted cross entropy is constructed, which is used to compare two discrete Z-numbers from the perspective of information entropy. Furthermore, one extended Technique for Order Preference by Similarity to Ideal Solution approach is developed to solve a multi-criteria decision-making problem under discrete Z-context. An example of the ranking of job candidates for human resource management is then presented to illustrate the availability of the proposed method along with the sensitivity and comparative analyses for verifying the validity and applicability of the proposed method.

Reliability analysis of distribution network of mining enterprises electrical power supply based on measure of information uncertainty

In the reliability analysis of the distribution network, information entropy is considered as the measure of uncertainty. The simple mathematical model that allows determining an entropy of a network structure is offered. The model is based on Shannon’s approach to the determination of information. Reliability analysis comes down to the comparison of two components of entropy: the first is the entropy of connection a source-electroreceiver in the structure; the second is a boundary entropy as information of observance of the requirement to support the required reliability level of electrical power supply of the electroreceiver. The example and the procedure how to perform the necessary calculations for the analysis are provided.

Ultrasound Statistical Parametric Imaging in the Assessment of Fatty Liver

Hepatitis steatosis may progress to nonalcoholic steatohepatitis, fibrosis, cirrhosis, and hepatocellular carcinoma. Nonalcoholic fatty liver disease (NAFLD) is the type of hepatic steatosis that most commonly leads to chronic liver disease. NAFLD is also related to metabolic risk factors. How to characterize fatty liver is attracting growing medical and health research interest. Notably, the speckle pattern is formed by ultrasound backscattered echoes, which are typically treated as random signals. Thus, analyzing the statistical distribution of the echo amplitude (i.e., the envelope signal) may provide useful clues associated with fatty liver diseases. Many investigators have began to study the relationship between the probability property of inverse scattering and the characteristics of tissue. Commonly used statistical models include the Rayleigh distribution, Rician distribution, K distribution, homodyned K distribution, Nakagami distribution, and compounding Nakagami distribution. One requisite of using statistical models to fit echo amplitude distributions is that the ultrasound envelope data must conform to the used distribution. To overcome the limitations mentioned above, we need to set a new direction for constructing the images of ultrasound parameters outside the statistical model ultrasonic method. Recall that Shannon established information theory and defined entropy as a measure of information uncertainty. Hughes pioneered using Shannon entropy for analyzing ultrasound signals, indicating that entropy is able to quantitatively describe changes in the microstructures of scattering media. Recently, we also developed the small-window entropy image of ultrasound by using a simple model of histograms and defined the weighted entropy to provide greater sensitivity in diagnosing the changes of the scattering microstructures of tissues. The results showed that fatty infiltration increases the uncertainty of backscattered signals from livers. Ultrasound entropy imaging has potential for the routine examination of fatty liver disease.

Portfolio construction based on information uncertainty measures and its effects on momentum return

One of the key areas of behavioral finance is investor's reaction to the uncertain environment in which is located where a series of factors, investor's individual and social psychology and experience, are involved in his/her decision-making. In fact, information uncertainty has been considered by different researchers as one of the realities of financial trade environment, particularly related to behavioral finance. To the extent that most of studies have recognized it as the basis of the formation of behavioral errors, including initial under-reaction (due to the conservatism and anchoring) or overreaction to the new released news that leads to momentum return. But there is no Consensus to measure information uncertainty. This study aimed to examine new measurement to determine information uncertainty based on firm specific factors. our results show that this method of, momentum portfolio construction leads more return comparing older method using other criteria for measuring information uncertainty.

Shannon Entropy Mapping of AF Rotors-Theoretical Extensions to a Novel Conceptual Paradigm

The pivot is critical to rotors maintaining AF. We have shown that high Shannon entropy (ShEn), a measure of information uncertainty, localises the pivot of rotors recorded with bipolar electrograms, and that targeted ablation of high ShEn EGMs is associated with termination in human AF This study evaluated ShEn colocalisation of rotors under conditions of: (i) rotor meander; (ii) electrogram filtering and (iii) effect of ShEn box size (iv) effect of myocyte model. Methods: Bipolar EGM recordings were studied in simulated (i) atrial (ii) ventricular and (iii) FitzHugh Nagumo rotors. Model meshes contained 100 × 100 elements with 0.5 mm spatial distance. Unipolar EGMs were calculated, which were used to construct bipolar EGMs. Spiral wave tip was localised with phase integration. ShEn was calculated as for each bipole. We simulated the effects of: (i) rotor meander, (ii) EGM filtering, with simulated high-pass Butterworth filters with cutoffs at 0.5, 10, and 30 Hz, (iii) ShEn box size in each model rotor system. Results: In each of the model systems, the highest region of ShEn colocalised with the pivoting region identified by the spiral wave tip. ShEn was inversely correlated with distance from the pivot (Pearson's r = −0.61, p < 0.001). The region of maximum Max ShEn colocalised with the pivot zone in ShEn box size from 0.01mV to 1 mV. Max ShEn remained colocalised with the pivot over a range of bipolar EGM cut-off frequencies, and with rotor meander, in each model system. Conclusion: These data confirm ShEn as a mechanistically based potential tool to map stable rotors.