A New Method for Symmetry Recognition in Boolean Functions Based on the Set-Theoretical Logic Differentiation. I

Rytsar, B.; Radioelectronics,

doi:10.15407/csc.2019.04.003

Cited by 2 publications

(1 citation statement)

References 15 publications

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“…Although artificial intelligence (AI) will help to solve the preprocessing tasks, such as gaps imputation, outliers analysis, complexity reduction, hidden dependencies finding etc. [4,5,6,7]. Artificial intelligence and Big Data will be used together for improving the prediction accuracy of spatial and temporal development of the disease in patients [8,9,10].…”

Section: Introductionmentioning

confidence: 99%

Data Driven Analytics for Personalized Medical Decision Making

Melnykova¹,

Shakhovska²,

ml.³

et al. 2020

Preprint

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The study was conducted on applying machine learning and data mining methods to personalizing the treatment. This allows investigating individual patient characteristics. Personalization is built on the clustering method and associative rules. It was suggested to determine the average distance between instances for optimal performance metrics finding. The formalization of the medical data pre-processing stage for finding personalized solutions based on current standards and pharmaceutical protocols is proposed. The model of patient data is built. The paper presents the novel approach to clustering built on ensemble of cluster algorithm with better than k-means algorithm Hopkins metrics. The personalized treatment usually is based on decision tree. Such approach requires a lot of computation time and cannot be paralyzed. Therefore, it is proposed to classify persons by conditions, to determine deviations of parameters from the normative parameters of the group, as well as the average parameters. This made it possible to create a personalized approach to treatment for each patient based on long-term monitoring. According to the results of the analysis, it becomes possible to predict the optimal conditions for a particular patient and to find the medicaments treatment according to personal characteristics.

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Section: Introductionmentioning

confidence: 99%

Data Driven Analytics for Personalized Medical Decision Making

Melnykova¹,

Shakhovska²,

ml.³

et al. 2020

Preprint

View full text Add to dashboard Cite

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Implementation of the method of figurative transformations to minimizing symmetric Boolean functions

Solomko¹,

Tadeyev²,

Zubyk

et al. 2021

EEJET

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This paper reports a study that has established the possibility of improving the effectiveness of the method of figurative transformations in order to minimize symmetrical Boolean functions in the main and polynomial bases. Prospective reserves in the analytical method were identified, such as simplification of polynomial function conjuncterms using the created equivalent transformations based on the method of inserting the same conjuncterms followed by the operation of super-gluing the variables. The method of figurative transformations was extended to the process of minimizing the symmetrical Boolean functions with the help of algebra in terms of rules for simplifying the functions of the main and polynomial bases and developed equivalent transformations of conjuncterms. It was established that the simplification of symmetric Boolean functions by the method of figurative transformations is based on a flowchart with repetition, which is the actual truth table of the assigned function. This is a sufficient resource to minimize symmetrical Boolean functions that makes it possible to do without auxiliary objects, such as Karnaugh maps, cubes, etc. The perfect normal form of symmetrical functions can be represented by binary matrices that would represent the terms of symmetrical Boolean functions and the OR or XOR operation for them. The experimental study has confirmed that the method of figurative transformations that employs the 2-(n, b)-design, and 2-(n, x/b)-design combinatorial systems improves the efficiency of minimizing symmetrical Boolean functions. Compared to analogs, this makes it possible to enhance the productivity of minimizing symmetrical Boolean functions by 100‒200 %. There are grounds to assert the possibility of improving the effectiveness of minimizing symmetrical Boolean functions in the main and polynomial bases by the method of figurative transformations. This is ensured, in particular, by using the developed equivalent transformations of polynomial function conjuncterms based on the method of inserting similar conjuncterms followed by the operation of super-gluing the variables.

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A New Method for Symmetry Recognition in Boolean Functions Based on the Set-Theoretical Logic Differentiation. I

Cited by 2 publications

References 15 publications

Data Driven Analytics for Personalized Medical Decision Making

Data Driven Analytics for Personalized Medical Decision Making

Implementation of the method of figurative transformations to minimizing symmetric Boolean functions

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