89 research outputs found

    Оценка приоритетов управлений на основе матрицы парных сравнений

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    The article contains a description of the model and approach for determining the weights of controls (other objects) based on a matrix of pairwise comparisons. The initial data in the matrix of paired comparisons implicitly specify interval estimates for comparison of controls. Interval estimates can be constructed relatively easily using Harrington's fuzzy metric scale. A heuristic method for determining the priorities of controls is proposed, which seeks to obtain weights (priorities) of controls that deviate minimally from the boundary values of the weight intervals.The latter are easy to find using the system of relations, on the basis of which the matrix of pairwise comparisons of controls is built. To assess the statistical adequacy of the found control priorities, the determination coefficient is used, the value of which at the level of 80 % and above is considered practically acceptable for applications. The critical value of the coefficient of determination can be determined, for example, using the Fisher criterion. If the conditions of statistical adequacy are not met, the initial data in the matrix of paired comparisons should be revised. An example is provided to illustrate the method described in the article. The main advantages of the approach described in the article are the flexibility of the choice of interval estimates for pairwise comparison of controls, the relative simplicity of computational calculations, and the ability to control the calculation results using statistical criteria. The described method develops the authors' approach to the adoption of anti-crisis management by adapting management priorities to the conditions of the production system and its environment.В статье содержится описание модели и подхода для определения весов управлений (иных объектов) на основе матрицы парных сравнений. Исходные данные в матрице парных сравнений в неявном виде задают интервальные оценки для сравнения управлений. Интервальные оценки можно сравнительно просто построить, используя нечеткую метрическую шкалу Харрингтона. Предлагается эвристический метод определения приоритетов управлений, который стремится получить веса (приоритеты) управлений, минимально отклоняющиеся от граничных значений интервалов весов. Последние легко отыскать с помощью системы отношений, на базе которых построена матрица парных сравнений управлений. Для оценки статистической адекватности найденных приоритетов управлений используется коэффициент детерминации, значение которого на уровне 80 % и выше считается практически приемлемым для приложений. Критическое значение коэффициента детерминации может быть определено, например, с помощью критерия Фишера. При невыполнении условий статистической адекватности следует пересмотреть исходные данные в матрице парных сравнений. Приведен пример, иллюстрирующий описанный в статье метод. Основными достоинствами изложенного в статье подхода являются гибкость выбора интервальных оценок при парном сравнении управлений, относительная простота вычислительных расчетов, возможность контроля результатов расчетов с помощью статистических критериев. Описанный метод развивает подход авторов к принятию антикризисных управлений за счет адаптации приоритетов управлений к условиям производственной системы и ее окружения

    Evaluation of Control Priorities Based on a Matrix of Paired Comparisons

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    В статье содержится описание модели и подхода для определения весов управлений (иных объектов) на основе матрицы парных сравнений. Исходные данные в матрице парных сравнений в неявном виде задают интервальные оценки для сравнения управлений. Интервальные оценки можно сравнительно просто построить, используя нечеткую метрическую шкалу Харрингтона. Предлагается эвристический метод определения приоритетов управлений, который стремится получить веса (приоритеты) управлений, минимально отклоняющиеся от граничных значений интервалов весов. Последние легко отыскать с помощью системы отношений, на базе которых построена матрица парных сравнений управлений. Для оценки статистической адекватности найденных приоритетов управлений используется коэффициент детерминации, значение которого на уровне 80 % и выше считается практически приемлемым для приложений. Критическое значение коэффициента детерминации может быть определено, например, с помощью критерия Фишера. При невыполнении условий статистической адекватности следует пересмотреть исходные данные в матрице парных сравнений. Приведен пример, иллюстрирующий описанный в статье метод. Основными достоинствами изложенного в статье подхода являются гибкость выбора интервальных оценок при парном сравнении управлений, относительная простота вычислительных расчетов, возможность контроля результатов расчетов с помощью статистических критериев. Описанный метод развивает подход авторов к принятию антикризисных управлений за счет адаптации приоритетов управлений к условиям производственной системы и ее окружения. The article contains a description of the model and approach for determining the weights of controls (other objects) based on a matrix of pairwise comparisons. The initial data in the matrix of paired comparisons implicitly specify interval estimates for comparison of controls. Interval estimates can be constructed relatively easily using Harrington's fuzzy metric scale. A heuristic method for determining the priorities of controls is proposed, which seeks to obtain weights (priorities) of controls that deviate minimally from the boundary values of the weight intervals.The latter are easy to find using the system of relations, on the basis of which the matrix of pairwise comparisons of controls is built. To assess the statistical adequacy of the found control priorities, the determination coefficient is used, the value of which at the level of 80 % and above is considered practically acceptable for applications. The critical value of the coefficient of determination can be determined, for example, using the Fisher criterion. If the conditions of statistical adequacy are not met, the initial data in the matrix of paired comparisons should be revised. An example is provided to illustrate the method described in the article. The main advantages of the approach described in the article are the flexibility of the choice of interval estimates for pairwise comparison of controls, the relative simplicity of computational calculations, and the ability to control the calculation results using statistical criteria. The described method develops the authors' approach to the adoption of anti-crisis management by adapting management priorities to the conditions of the production system and its environment

    Принятие решений на основе условной нечеткой меры

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    The application of a conditional logical formula of three-valued calculus in the decision-making system is considered. A conditional logical formula makes it possible to determine a conditional fuzzy measure on its basis, which is associated with the following positive aspects. First, there is no need for expert evaluation of the fuzzy measure of the truth of the conclusion for fuzzy premises, which reduces the degree of subjectivity and eliminates the need to ensure the completeness of statistical data, as well as the justification of completeness. Secondly, the proposed version of calculating conditional conclusions relatively simply allows for a multi-premise case and the ability to evaluate the importance of premises based on their priorities (in classical approaches like Mamdani, premises do not differ in their degree of importance for conclusions). Thirdly, there is no needto eva luate the degree of truth of the rules themselves for fuzzy conclusions. These advantages simplify practical use and ultimately improve the quality of decisions made, especially in the case of a large number of inputs (for exam ple, numbered in tens). An example of the practical use of the approach developed on the basis of a fuzzy conditional measure for making decisions about the correction of the learning process based on the testing results is given.Рассмотрено применение уcловной логической формулы трехзначного исчисления в системе принятия решений. Такая формула дает возможность определения на ее основе условной нечеткой меры, что связано со следующими положительными моментами. Во-первых, отпадает необходимость в экспертном оценивании нечеткой меры истинности заключения для нечетких посылок, что уменьшает степень субъективности и устраняет необходимость обеспечения полноты статистических данных, а также обоснование полноты. Во-вторых, предлагаемый вариант вычисления условных заключений сравнительно просто допускает многопосылочный случай и возможность оценивать важность посылок на основе их приоритетов (в классических подходах типа Мамдани посылки не различаются по степени их важности для заключений). В-третьих, нет необходимости оценивать степень истинности самих правил для нечетких заключений. Указанные достоинства упрощают практическое использование и, в конечном итоге, повышают качество принимаемых решений, особенно в случае большого числа входных посылок (например, исчисляемого десятками). Приводится пример практического использования развиваемого на основе нечеткой условной меры подхода для принятия решений о коррекции процесса обучения по результатам тестирования

    The case for strategic international alliances to harness nutritional genomics for public and personal health

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    Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene-nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient-genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countrie

    Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

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    Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

    Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

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    Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

    Search for pair production of excited top quarks in the lepton+jets final state

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    Horizons in nutritional science : The case for strategic international alliances to harness nutritional genomics for public and personal health.

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    Nutrigenomics is the study of how constituents of the diet interact with genes, and their products, to alter phenotype and, conversely, how genes and their products metabolise these constituents into nutrients, antinutrients, and bioactive compounds. Results from molecular and genetic epidemiological studies indicate that dietary unbalance can alter gene–nutrient interactions in ways that increase the risk of developing chronic disease. The interplay of human genetic variation and environmental factors will make identifying causative genes and nutrients a formidable, but not intractable, challenge. We provide specific recommendations for how to best meet this challenge and discuss the need for new methodologies and the use of comprehensive analyses of nutrient–genotype interactions involving large and diverse populations. The objective of the present paper is to stimulate discourse and collaboration among nutrigenomic researchers and stakeholders, a process that will lead to an increase in global health and wellness by reducing health disparities in developed and developing countries
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