Uncertainty Zones Research Articles

Discourse factor of semantic uncertainty in reverse machine translation of media texts

The article is devoted to the study of semantic uncertainty in the texts of legal and media discourses using online programs. The object of the study is conflict factors caused by semantic uncertainty in problem areas. An assessment and description of problem areas in machine translation of media texts was carried out, taking into account lexical ambiguity. The prerequisites for possible conflict situations when translating texts on legal and environmental topics are described. In achieving this goal, both traditional linguistic and innovative methods of analysis (use of artificial intelligence technologies) were used. The characteristics of the philosophical category of uncertainty are given according to the following methodology: 1) assessment of the semantic uncertainty of reverse machine translation texts, taking into account the discursive factor; 2) comparison of legislative and media texts for their similarity to the original after machine translation. The comparative analysis took into account the following parameters: the total number of words in the texts; similarity of texts in percentage terms; presence of various fragments. It is shown that discursive and linguistic means of realizing semantic uncertainty have a significant impact on the reader’s perception of the text. A comparison of two discourses of the same thematic focus on environmental management revealed the influence of the context (discourse) and the intermediary language on the degree of translatability of the text. It has been established that semantic uncertainty and tension zones as conflict-generating factors depend on the quality of translation programs. The study took into account possible errors associated with the limited capabilities of the online programs used. Prospects for studying problem areas in reverse machine translation include expanding sources of empirical material, involving other computer-assisted translation systems, and the possibility of applying research results in an expanded context of “potential conflict”.

An algorithmic approach to identification of gray areas: Analysis of sleep scoring expert ensemble non agreement areas using a multinomial mixture model

Machine learning (ML) models have become a key component in modern world services. In decision-making domains where human expertise is crucial, for example, for manually scoring biological signal data, human uncertainties undermine experts’ trust in the outcomes of these models. The field of sleep staging in particular, which requires experts to score complex biological signal is notably impacted by scoring uncertainties. Data consisting of an ensemble of independent scorers are collected to estimate inter scorer agreement and the uncertainty associated with manual scoring. However, scorers’ uncertainty lacks statistical modeling, which poses difficulties in validating ML algorithms and leads to issues of reliability and explainability. From the ensemble of scorers, uncertainty zones, called gray areas, are highlighted by samples where scorers disagree. The objective of our work is to provide a framework introducing and inferring gray areas. We present a flexible and easy-to-use multi-objective method based on multinomial mixture models clustering the different levels of scorer agreement and summarize the results into two sets of high-agreement and gray area clusters, which are called supra-clusters. The threshold is selected according to the maximization of the distance between two distributions of scorers agreement measure. Effective results were obtained by the method after it was fitted on simulated data. Additionally, the method was applied to a real case of uncertainty analysis in the sleep staging domain. A series of actual sleep stages scored by an ensemble of 10 independent scorers for a dataset of 50 participants was used.

One-terminal traveling wave-based transmission line protection for LCC-HVDC systems

This paper proposes a one-terminal traveling wave (TW)-based transmission line protection for line commutated converter (LCC) of high-voltage direct current (HVDC) systems. The method requires the first and second wavefronts to reach the local bus and considers the boundary conditions of the system. A detailed mathematical analysis of the sampling frequency effects, as the basis for a number of innovations of practical interest, is presented here. Firstly, a definition of a minimum sampling frequency is formulated. This is crucial when dealing with the high sampling frequencies traditionally needed by TW-based methods. Secondly, mathematical expressions of protected, unprotected, and uncertainty zones on the transmission line are defined. Thanks to these calculations, the method is also capable of distinguishing faults at the line terminals from faults on the protected transmission line. Thirdly, the non-requirement for the TW propagation speed estimation is proven. Some TW-based protection elements require knowledge of the TW propagation speed, which is a source of errors. The proposed function presented good dependability and was able to operate below 15 ms for a transmission line of 2900 km in length.

Mapping Flood Risk Uncertainty Zones in Support of Urban Resilience Planning

<p>River flooding and urbanization are processes of different character that take place worldwide. As the latter tends to make the consequences of the former worse, together with the uncertainties related to future climate change and flood-risk modeling, there is a need to both use existing tools and develop new ones that help the management and planning of urban environments. In this article a prototype tool, based on estimated maximum land cover roughness variation, the slope of the ground, and the quality of the used digital elevation models, and that can produce flood ‘uncertainty zones’ of varying width around modeled flood boundaries, is presented. The concept of uncertainty, which urban planners often fail to consider in the spatial planning process, changes from something very difficult into an advantage in this way. Not only may these uncertainties be easier to understand by the urban planners, but the uncertainties may also function as a communication tool between the planners and other stakeholders. Because flood risk is something that urban planners always need to consider, these uncertainty zones can function both as buffer areas against floods, and as blue-green designs of significant importance for a variety of ecosystem services. As the Earth is warming and the world is urbanizing at rates and scales unprecedented in history, we believe that new tools for urban resilience planning are not only urgently needed, but also will have a positive impact on urban planning.</p>

Digital Regulation of Intellectual Capital for Open Innovation: Industries’ Expert Assessments of Tacit Knowledge for Controlling and Networking Outcome

Digital regulation implies the quantified measuring and the network infrastructure allowing managers to control the processes of value creation. Digital regulation needs to take into account tacit elements of the value creation process, including unconscious competency, creativity, and intuitive anticipation, to assure the resulting network’s innovation growth. Digital society in developing countries is built on the ground of fact change of the economy and social relations, of transition towards an emerging market within the global offline network of interactions and online activities through Internet; the innovative growth imposes the evolution of managerial behavior and attitudes. The main objective of the paper is to obtain indications on the perception of intellectual capital by corporate managers. The exploratory study was carried out in Russian companies operating in different sectors, with the use of the open-ended approach, including focused interviews and group discussion among experts, middle and senior managers from marketing or corporate governance background. The data were complemented by documentary analysis of descriptions of internal processes of the implementation of digital tools of accounting, which includes the human resources control applied for the remote work during the pandemic. Networking helps to coordinate functions between team members at remote work and between teams and administrators. The interviews demonstrated the administrative tendency to under-estimate the non-formalized factors of innovation activity, such as awareness of corporate strategy, creativity, motivation, and affective and behavioral components of communication of the persons involved in the enrichment of intellectual capital. The results show fuzzy boundaries between the intellectual capital components that are difficult to control. This difficulty provokes the preference for the use of “traditional” quantitative indicators that had been implemented at the stage of the financial digitalization, instead of developing new parameters or measuring approaches. The networking emerges synergetic effect if the administrators refuse their monopoly on the uncertainty zones and are oriented to construct the trustful atmosphere of personal responsibility within the network.

Theory of the technological machine state recognition by the criterion of resource uncertainty

The solution to the problems of assessing the technical condition of special equipment is presented at a multidisciplinary level, as a combination of scientific and technical, practice-oriented research. The purpose of study: development of a digital mechanism for assessing the uncertainty of the state of special equipment systems with real-time monitoring of the intensity of parameter changes, recognition and predictive notification of the probability of risk-failure. It has been established that, in accordance with the theory of probability, there can be only one failure in a unit at a time, even if several damages are diagnosed, and then there is always a single cause. The introduction of the concept of “integrated parameter” supplemented the characteristics of functional and structural multiparameter connections of the state of the unit and made it possible to substantiate the mechanism for recognizing the uncertainty of the state of special equipment systems as a whole. A diagnostic model has been built based on the use of the main provisions of information theory, which represents the unit as a system containing the risk of uncertainty in terms of failure, which is distributed over all structural elements of the unit. An algorithm for recognizing the spatial displacement of uncertainty zones is proposed, the translation of which into a digital format with the introduction of a characteristic criterion will provide a search for a defect (risk-failure). The practical implementation of the risk-failure recognition mechanism is carried out on a simulation model of a change in the state of a technical system using the example of a cardan joint of a technological machine, which is under severe operating conditions during reclamation work. The inclusion in the design of technological machines of a digital module for monitoring the technical condition of the unit is substantiated, including: a module for recognizing the elemental structure; a software shell with a calculation algorithm for evaluating parametric changes; module of interface predictive notification of risk-failure; service control module by state.

Analysis of the covariance matrix in FWI through density of covariance maps

Full waveform inversion (FWI) is a tool for the inversion of seismic data. There are several sources of uncertainty in the results provided by FWI. The quantification of such uncertainties has been studied through the resolution matrix (Res), which rests on a quadratic approximation that interprets the Hessian matrix as the posterior covariance matrix. Despite efforts in the use of Res, there is no published analysis of the uncertainties contained in the full correlation matrix, (R). Our approach leads to build the full R matrix, which, at the end of the day, is the final quantity that includes all the information associated with uncertainties.We focused on uncertainties related to variation in the starting models of the FWI, and thus propose a method to study the full R matrix, which is-called the Density of Correlation Map, D. By using the D map, we found that the highest uncertainty zones in the FWI inverted model are near the sources, the model boundaries, and the interfaces. We argue that D can be a complement for the study and estimation of uncertainties in FWI.

Use of Uncertainty Zones for Vessel Operation in Inland Waterways

European inland waterways represent an underutilised avenue of transport. Increased use of this avenue has the possibility to decrease emissions and remove traffic from congested roadways. However, there is a shortage of skilled shippers and labour costs threaten to make waterway transport economically unviable. By creating smart ships, the requirement for skilled shippers decreases. The Hull-to-Hull (H2H) project, part of the European Horizon 2020 program, aims to do this through various methods, one of which is the creation of a smart ship navigation system. This system makes use of uncertainty zones in its display and control software to assist a vessel’s helmsman in making safe navigation decisions. Based on the ship’s dynamics and current operating scenario, the uncertainty zones will change shape and size, and different notifications will be given to the helmsman based on the overlapping of the uncertainty zones. This paper focusses on the uncertainty zone based navigation system currently being developed for the inland waterway use case.

Discrimination of extra virgin olive oils from five French cultivars: En route to a control chart approach

The control of varietal origin is an important issue to insure the authenticity of olive oils. In this study, extra virgin olive oils from five French cultivars were discriminated by applying partial least square discriminant analysis (PLS1-DA) to their fatty acid and squalene compositions obtained by gas chromatography. Two decision rules were compared to determine the varietal origin of predicted samples: either a classical PLS-DA approach with uncertainty zones, or a control chart approach with warning and control limits. The control chart approach, being focused on characteristic samples from each modelled cultivar, is able to deal with classes having unbalanced number of samples and to identify atypical samples.

A Practice-Oriented Bifurcation Analysis for Pulse Energy Converters. Part 3: Transients

The paper continues the discussion on the bifurcation analysis conceptions for applications in practice-oriented solutions for pulse energy conversion systems (PEC-systems). This viewpoint means an attempt to resolve so-called conflict-of-units between the notions used to describe natural evolution (i.e. evolution of the operating process towards nonoperating processes and vice versa) and the notions used to describe a desirable artificial regime (i.e. the operating regime). In this connection, the correspondence between causes (degradation of the operating process stability) and effects (changes of the operating characteristics) is established in the following sequence: nonlinear dynamics output signal operating characteristics, where these characteristics include stability and performance. Two starting points follow from the previous parts. First, there are distinguishable thresholds of evolutional degradation, between which the operating process loses stability in a particular manner; and these particularities can be systematized by means of so-called uncertainty zones. Second, multi-D integrating translations of phase images with regular parametrical variation are combined with the corresponding boundaries of the operating stability and performance by means of the modified bifurcation diagrams. Then we focus on the basic characteristics of transients and first demonstrate and discuss some unified form of the modified bifurcation diagrams, to which a solution on the operating performance can be reduced. Namely, we show such solutions for an overshoot and a settling time in comparison with a control error. We believe that the practice-oriented bifurcation analysis could be interesting to pioneer research intended for the design of promising systems of pulse energy conversion.

Author Correction: Biomass-based negative emissions difficult to reconcile with planetary boundaries

In the version of this Letter originally published, in Fig. 2, the labels for the yellow and green areas were swapped: the yellow areas should have been labelled ‘Global uncertainty zones’ and the green areas should have been labelled ‘Global safe zones’. This has now been corrected in the online versions of the Letter.

Mapping units based on spatial uncertainty of magnetic susceptibility and clay content

This study aimed to use spatial uncertainty of magnetic susceptibility (MS) and clay content to improve soil-mapping units. In an experimental area of 870ha, a regular sampling grid containing 371 points was set, in which MS and clay content were assessed at a depth range of 0–0.25m. Using a digital elevation model and field observations, a 4440-m transect was established on the study area from hilltop to the foothill, toward the gentlest slope. Standard deviation maps based on 200 realizations of the sequential gaussian simulation measured spatial estimate uncertainties. To limit transition zones along the transect, uncertainty isolines representative of the transition between soil-mapping units were selected. Both attributes presented peaks of uncertainties near the change of mapping units, previously known. Uncertainty zones, previously delineated, ranged from 45 to 210m and from 60 to 170m, for MS and clay content, respectively. However, after extrapolating the uncertainties to the side of the transect, amplitude changes of the uncertainty zones were observed, especially in the transition regions between landscape shape and geology. Delineation of mapping units, which incorporated the uncertainties of MS and clay content, was similar. However, due to lower cost and promptness, MS becomes the most feasible alternative. Knowing spatial uncertainties enables readjusting limits in maps of soil-mapping units and may support identification of most favorable regions for determining modal pedon representative of each unit.

Visualising DEM-related flood-map uncertainties using a disparity-distance equation algorithm

Abstract. The apparent absoluteness of information presented by crisp-delineated flood boundaries can lead to misconceptions among planners about the inherent uncertainties associated in generated flood maps. Even maps based on hydraulic modelling using the highest-resolution digital elevation models (DEMs), and calibrated with the most optimal Manning's roughness (n) coefficients, are susceptible to errors when compared to actual flood boundaries, specifically in flat areas. Therefore, the inaccuracies in inundation extents, brought about by the characteristics of the slope perpendicular to the flow direction of the river, have to be accounted for. Instead of using the typical Monte Carlo simulation and probabilistic methods for uncertainty quantification, an empirical-based disparity-distance equation that considers the effects of both the DEM resolution and slope was used to create prediction-uncertainty zones around the resulting inundation extents of a one-dimensional (1-D) hydraulic model. The equation was originally derived for the Eskilstuna River where flood maps, based on DEM data of different resolutions, were evaluated for the slope-disparity relationship. To assess whether the equation is applicable to another river with different characteristics, modelled inundation extents from the Testebo River were utilised and tested with the equation. By using the cross-sectional locations, water surface elevations, and DEM, uncertainty zones around the original inundation boundary line can be produced for different confidences. The results show that (1) the proposed method is useful both for estimating and directly visualising model inaccuracies caused by the combined effects of slope and DEM resolution, and (2) the DEM-related uncertainties alone do not account for the total inaccuracy of the derived flood map. Decision-makers can apply it to already existing flood maps, thereby recapitulating and re-analysing the inundation boundaries and the areas that are uncertain. Hence, more comprehensive flood information can be provided when determining locations where extra precautions are needed. Yet, when applied, users must also be aware that there are other factors that can influence the extent of the delineated flood boundary.

Experimental Identification of Uncertainties in Dynamics of PWM Buck Converter

The paper is dedicated to the development of experimental bifurcation analysis and is focused on the research of uncertainties in dynamics of an operating process in application to PWM buck converters. The experimental bifurcation analysis follows the approach which allows to identify some qualitative thresholds through the successive evolution of the system behaviour caused by the complex interplay between bifurcation and noise components. In according to the approach the 2D-operating process domain is built and is divided onto three kinds of the uncertainty zones. The computational and experimental results are discussed from the practical experience concerning the ways to prevent the abnormal processes in dynamics of PWM buck converters.

Improved vehicle classification from dual-loop detectors in congested traffic

Vehicle classification is an important traffic parameter for transportation planning and infrastructure management. Length-based vehicle classification from dual loop detectors is among the lowest cost technologies commonly used for collecting these data. Like many vehicle classification technologies, the dual loop approach works well in free flow traffic. Effective vehicle lengths are measured from the quotient of the detector dwell time and vehicle traversal time between the paired loops. This approach implicitly assumes that vehicle acceleration is negligible, but unfortunately at low speeds this assumption is invalid and length-based classification performance degrades in congestion.To addresses this problem, we seek a solution that relies strictly on the measured effective vehicle length and measured speed. We analytically evaluate the feasible range of true effective vehicle lengths that could underlie a given combination of measured effective vehicle length, measured speed, and unobserved acceleration at a dual loop detector. From this analysis we find that there are small uncertainty zones where the measured length class can differ from the true length class, depending on the unobserved acceleration. In other words, a given combination of measured speed and measured effective vehicle length falling in the uncertainty zones could arise from vehicles with different true length classes. Outside of the uncertainty zones, any error in the measured effective vehicle length due to acceleration will not lead to an error in the measured length class. Thus, by mapping these uncertainty zones, most vehicles can be accurately sorted to a single length class, while the few vehicles that fall within the uncertainty zones are assigned to two or more classes. We find that these uncertainty zones remain small down to about 10mph and then grow exponentially as speeds drop further.Using empirical data from stop-and-go traffic at a well-tuned loop detector station the best conventional approach does surprisingly well; however, our new approach does even better, reducing the classification error rate due to acceleration by at least a factor of four relative to the best conventional method. Meanwhile, our approach still assigns over 98% of the vehicles to a single class.

Climate Change Impacts on Flood Events and Its Consequences on Human in Deba River

The scientific community agrees that climate change is one of the greatest challenges that oursociety will have to face this century. Indeed, the fourth report from the Intergovernmental Panel on ClimateChange (IPPC) confirms the certitude of this phenomenon and its impacts, which can range from droughts tofloods, health problems and food shortages. The principal objective of this paper is to assess the impact ofclimate change on flood events and its consequences on human. This point is necessary to define and evaluate different adaptation options. Even taking into account the medium greenhouse emission scenario, according to the results, it is expected that extreme precipitation will increase during the twenty century, although there is an uncertainty in the percentage due to the climatic models. It is expected an increase in peak discharge between 14±9 and 15±8 for 3 models and for the period 2001-2040 with a return period exceeding 40 years. For the period 2041-2080 there is more uncertainty, it is expected an increase between 12±8 and 19±10 for 2 models. According to the results, changes in flood event are expected with its associated uncertainty and new flood zones are detected with greater hazard to people.

Evaluation of the impact of the time synchronization accuracy of multistatic radar positions on errors in determining the spatial coordinates of aerial objects

Amethod for evaluating the impact of the time synchronization accuracy of multistatic radar positions on errors in determining the spatial coordinates of aerial objects has been proposed. The investigation of the influence of the characteristics of time references and their synchronization methods on the size of spatial uncertainty zones of object position for multistatic radars in the “delta” and “three-rayed star” configurations was carried out by using the developed models and the method of statistical simulation modeling. The above investigation involved the use of the time-of-arrival and time-difference-of arrival techniques of coordinate determination.

Uncertain lines and circles with dependencies

Classical computational geometry algorithms handle geometric constructs whose shapes and locations are exact. However, many real-world applications require the modeling of objects with geometric uncertainties. Existing geometric uncertainty models cannot handle dependencies among objects. This results in the overestimation of errors. We have developed the Linear Parametric Geometric Uncertainty Model, a general, computationally efficient, worst-case, linear approximation of geometric uncertainty that supports dependencies among uncertainties. In this paper, we present the properties of the uncertainty zones of a line and circle, defined using this model, and describe efficient algorithms to compute them. We show that the line’s envelope has linear space complexity and is computed in low polynomial time. The circle’s envelope has quadratic complexity and is also computed in low polynomial time.

A New Approach for the Dynamics of Ultra-High-Frequency Data: The Model with Uncertainty Zones

In this paper, we provide a model which accommodates the assumption of a continuous efficient price with the inherent properties of ultra-high-frequency transaction data (price discreteness, irregular temporal spacing, diurnal patterns...). Our approach consists in designing a stochastic mechanism for deriving the transaction prices from the latent efficient price. The main idea behind the model is that, if a transaction occurs at some value on the tick grid and leads to a price change, then the efficient price has been close enough to this value shortly before the transaction. We call uncertainty zones the bands around the mid-tick grid where the efficient price is too far from the tick grid to trigger a price change. In our setting, the width of these uncertainty zones quantifies the aversion to price changes of the market participants. Furthermore, this model enables us to derive approximated values of the efficient price at some random times, which is particularly useful for building statistical procedures. Convincing results are obtained through a simulation study and the use of the model over 10 representative stocks.

A multiparameter converter for recording the location of an air leak from the international space station

A multiparameter instrument for recording the location of an air leak from the space station module, based on three sensors, namely, electret, thermocouple and an ionization separator, is proposed. The regions of greatest reliability of the measurements of each of the sensors are determined and the recorded air leak uncertainty zones are pointed out.