Method of Assessing the Integral Risk on the Example of the system «GL2Z Enterprise — Hazardous and Harmful Factors — Employees»

The Algerian company Sonatrach is associated with the production of the liquefied natural gas, propane, butane, gasoline from the crude gas. The article solves the problem of assessing the integral risk at the GL2Z natural gas liquefaction plant with an analysis of the possible joint effect on the employees of production products complex as harmful and (or) hazardous factors in the form of chemical and thermal factors, provided that a fire or flash occurs considering the error of measuring gas components concentration. Integral risk is understood as probable (expected) damage from the occurrence of an incident or from the realization of an unfavorable outcome, provided that the full group of possible incidents (outcomes) in the system under consideration is considered. Modeling and cause-and-effect analysis of the occurrence of an incident and (or) adverse outcomes in the system is described using factor parametric models of the type «load-bearing capacity», «effect — susceptibility». In this case, most often the realization of an unfavorable outcome is evaluated by the condition of exceeding the parameter or the magnitude of the effect over the susceptibility parameter. Using the example of the system under consideration, a Boolean function of the integral risk indicator is constructed, and a demonstration of the calculation of its probabilistic form is performed. In addition, it is proposed to calculate a probabilistic measure from a unified position of logical and parametric description of both the set of possible incidents and their components in the form of unfavorable outcomes. To test the proposed method for assessing the integral risk, the initial data were used, with which, provided that the probability of an outbreak of all five components of the crude gas is equal, it was obtained that in a particular analyzed system, the calculated value of the upper limit of the probability of an incident occurrence was 0.9675.

aggreCAT: An R Package for Mathematically Aggregating Expert Judgments

Structured protocols, such as the IDEA protocol, may be used to elicit expert judgments in the form of subjective probabilities from multiple experts. Judgments from individual experts about a particular phenomena must therefore be mathematically aggregated into a single prediction. The process of aggregation may be complicated when uncertainty bounds are elicited with a judgment, and also when there are several rounds of elicitation. This paper presents the new R package \pkg{aggreCAT}, which provides 22 unique aggregation methods for combining individual judgments into a single, probabilistic measure. The aggregation methods were developed as a part of the Defense Advanced Research Projects Agency (DARPA) ‘Systematizing Confidence in Open Research and Evidence’ (SCORE) programme, which aims to generate confidence scores or estimates of ‘claim credibility’ for 3000 research claims from the social and behavioural sciences. We provide several worked examples illustrating the underlying mechanics of the aggregation methods. We also describe a general workflow for using the software in practice to facilitate uptake of this software for appropriate use-cases.

Elements of probability theory with values in bihyperbolic algebra

In this paper we expand the concept of a really significant probabilistic measure in the case when the measure takes values in the algebra of bihyperbolic numbers. The basic properties of bihyperbolic numbers are given, in particular idempotents, main ideals generated by idempotents, Pierce's decompo\-sition and the set of zero divisors of the algebra of bihyperbolic numbers are determined. We entered the relation of partial order on the set of bihyperbolic numbers, by means of which the bihyperbolic significant modulus is defined and its basic properties are proved. In addition, some bihyperbolic modules can be endowed with a bihyperbolic significant norms that take values in a set of non-negative bihyperbolic numbers. We define $\sigma$-additive functions of sets in a measurable space that take appropriately normalized bihyperbolic values, which we call a bihyperbolic significant probability. It is proved that such a bihyperbolic probability satisfies the basic properties of the classical probability. A representation of the bihyperbolic probability measure is given and its main properties are proved. A bihyperbolically significant random variable is defined on a bihyperbolic probability space, and this variable is a bihyperbolic measurable function in the same space. We proved the criterion of measurability of a function with values in the algebra of bihyperbolic numbers, and the basic properties of bihyperbolic random variables are formulated and proved. Special cases have been studied in which the bihyperbolic probability and the bihyperbolic random variable take values that are zero divisors of bihyperbolic algebra. Although bihyperbolic numbers are less popular than hyperbolic numbers, bicomplex numbers, or quaternions, they have a number of important properties that can be useful, particularly in the study of partial differential equations also in mathematical statistics for testing complex hypotheses, in thermodynamics and statistical physics.

Quantifying ambiguity in sea-level projections

<p>Coastal impacts of climate change and the related mitigation and adaptation needs requires assessments of future sea-level changes. Following a common practice in coastal engineering, probabilistic sea-level projections have been proposed for at least 20 years. This requires a probability model to represent the uncertainties of future sea-level rise, which is not achievable because potential ice sheets mass losses remain poorly understood given the knowledge available today. Here, we apply the principles of extra-probabilistic theories of uncertainties to generate global and regional sea-level projections based on uncertain components. This approach assigns an imprecision to a probabilistic measure, in order to quantify lack of knowledge pertaining to probabilistic projections. This can serve to understand, analyze and communicate uncertainties due to the coexistence of different processes contributing to future sea-level rise, including ice-sheets. We show that the knowledge gained since the 5th Assessment report of the IPCC allows better quantification of how global and regional sea-level rise uncertainties can be reduced with lower greenhouse gas emissions. Furthermore, Europe and Northern America are among those profiting most from a policy limiting climate change to RCP 2.6 versus RCP 4.5 in terms of reducing uncertainties of sea-level rise.</p>

Improvement on the association strength: implementing a probabilistic measure inspired on combinations without repetition.

The use of co-occurrence data is common in various domains. Co-occurrence data often needs to be normalised to correct for the size-effect. To this end, van Eck and Waltman (2009) recommend a probabilistic measure known as the association strength. However, this formula, based on combinations with repetition, implicitly assumes that observations from the same entity can co-occur even though in the intended usage of the measure these self-co-occurrences are non-existent. A more accurate measure inspired on combinations without repetition is introduced here and compared to the original formula in mathematical derivations, simulations, and patent data, which shows that the original formula overestimates the relation between a pair and that some pairs are more overestimated than others. The new measure is available in the EconGeo package for R maintained by Balland (2016). Peer Review https://publons.com/publon/10.1162/qss_a_00122

The Role of Parental Input in the Early Acquisition of Japanese Politeness Distinctions

Japanese polite language (teineigo) varies with the speaker-addressee relationship as well as social norms. Descriptive studies have found that young Japanese children use polite-speech early in development. This claim was experimentally tested in 3- to 6-year-old Japanese children and correct use of polite verb forms was found even in the youngest children. The early acquisition of these verb forms is surprising, because there is a Japanese social norm that parental speech to children is mostly not polite, so it is not clear how children acquire the knowledge of how to use polite forms. To examine this, a large scale corpus analysis of polite language was performed using a probabilistic measure of the intended addressee. We confirmed that parental speech is mostly not polite, but parents also produced a substantial amount of polite language that varied appropriately with addressees and this can help to explain the early use of polite speech in Japanese children under experimental conditions.

Determination of Integrated Safety of High-Risk Structures According to Criteria of Acceptable and Manageable Risks

The paper considers the transition from traditional methods and systems for determining the standard and limit states of potentially dangerous objects by criteria of strength, resource and reliability to new perspective methods for assessing the risks of managing them. The conditions for ensuring the complex safety and security of the equipment and high-risk structures by the criteria of acceptable and managed risks are determined. It is established that the level of risk for assessing the safety status of a potentially dangerous object is defined as a probabilistic measure of the occurrence of man-made or natural phenomena, which are accompanied by the formation and action of harmful factors, as well as inflicted social, environmental, economic and other kinds of losses.

POSFUST RELIABILITY OF A NON-REPAIRABLE MULTI-STATE SYSTEM WITH POSFUST FAILURE RATE ESTIMATION

Present research paper attempts to estimate the posfust reliability of a non-repairable multi-state system (NRMSS). Failure rate estimation is key factor in the reliability estimation. But due to uncertainty in the environment and probabilistic measure, the absolute measurement of the failure rate is quite tedious. In this research paper, we have introduced a new measure for failure rate estimation using possibilistic measure based on fuzzy logic. In this work for the effective measurements of reliability, we have tried to cover the uncertainty in the failure rate at every state failure level. In this research paper, we have taken a non-repairable three state system and failure rate transition of every state is taken in the form of upper and lower bound in possibilistic measure. In this approach, Markov process (multi-state system) is used for getting the governing differential equation for transition from one state to another state. Numerical computations are also being carried out to estimate the posfust reliability.